Electrophysiological and behavioral correlates of stable automatic semantic retrieval in aging

Previous studies have shown both declining and stable semantic-memory abilities during healthy aging. There is consistent evidence that semantic processes involving controlled mechanisms weaken with age. In contrast, results of aging studies on automatic semantic retrieval are often inconsistent, probably due to methodological limitations and differences. The present study therefore examines age-related alterations in automatic semantic retrieval and memory structure with a novel combination of critical methodological factors, i.e., the selection of subjects, a well-designed paradigm, and electrophysiological methods that result in unambiguous signal markers. Healthy young and elderly participants performed lexical decisions on visually presented word/non-word pairs with a stimulus onset asynchrony (SOA) of 150 ms. Behavioral and electrophysiological data were measured, and the N400-LPC complex, an event-related potential component sensitive to lexical-semantic retrieval, was analyzed by power and topographic distribution of electrical brain activity. Both age groups exhibited semantic priming (SP) and concreteness effects in behavioral reaction time and the electrophysiological N400-LPC complex. Importantly, elderly subjects did not differ significantly from the young in their lexical decision and SP performances as well as in the N400-LPC SP effect. The only difference was an age-related delay measured in the N400-LPC microstate. This could be attributed to existing age effects in controlled functions, as further supported by the replicated age difference in word fluency. The present results add new behavioral and neurophysiological evidence to earlier findings, by showing that automatic semantic retrieval remains stable in global signal strength and topographic distribution during healthy aging.

A Comparative Study of Two Semantic Systems: Body Russian and Russian Phraseology

Grigorij Kreidlin (Russia). A Comparative Study of Two Semantic Systems: Body Russian and Russian Phraseology. Mr. Kreidlin teaches in the Department of Theoretical and Applied Linguistics of the State University of Humanities in Moscow and worked on this project from August 1996 to July 1998. The classical approach to non-verbal and verbal oral communication is based on a traditional separation of body and mind. Linguists studied words and phrasemes, the products of mind activities, while gestures, facial expressions, postures and other forms of body language were left to anthropologists, psychologists, physiologists, and indeed to anyone but linguists. Only recently have linguists begun to turn their attention to gestures and semiotic and cognitive paradigms are now appearing that raise the question of designing an integral model for the unified description of non-verbal and verbal communicative behaviour. This project attempted to elaborate lexical and semantic fragments of such a model, producing a co-ordinated semantic description of the main Russian gestures (including gestures proper, postures and facial expressions) and their natural language analogues. The concept of emblematic gestures and gestural phrasemes and of their semantic links permitted an appropriate description of the transformation of a body as a purely physical substance into a body as a carrier of essential attributes of Russian culture - the semiotic process called the culturalisation of the human body. Here the human body embodies a system of cultural values and displays them in a text within the area of phraseology and some other important language domains. The goal of this research was to develop a theory that would account for the fundamental peculiarities of the process. The model proposed is based on the unified lexicographic representation of verbal and non-verbal units in the Dictionary of Russian Gestures, which the Mr. Kreidlin had earlier complied in collaboration with a group of his students. The Dictionary was originally oriented only towards reflecting how the lexical competence of Russian body language is represented in the Russian mind. Now a special type of phraseological zone has been designed to reflect explicitly semantic relationships between the gestures in the entries and phrasemes and to provide the necessary information for a detailed description of these. All the definitions, rules of usage and the established correlations are written in a semantic meta-language. Several classes of Russian gestural phrasemes were identified, including those phrasemes and idioms with semantic definitions close to those of the corresponding gestures, those phraseological units that have lost touch with the related gestures (although etymologically they are derived from gestures that have gone out of use), and phrasemes and idioms which have semantic traces or reflexes inherited from the meaning of the related gestures. The basic assumptions and practical considerations underlying the work were as follows. (1) To compare meanings one has to be able to state them. To state the meaning of a gesture or a phraseological expression, one needs a formal semantic meta-language of propositional character that represents the cognitive and mental aspects of the codes. (2) The semantic contrastive analysis of any semiotic codes used in person-to-person communication also requires a single semantic meta-language, i.e. a formal semantic language of description,. This language must be as linguistically and culturally independent as possible and yet must be open to interpretation through any culture and code. Another possible method of conducting comparative verbal-non-verbal semantic research is to work with different semantic meta-languages and semantic nets and to learn how to combine them, translate from one to another, etc. in order to reach a common basis for the subsequent comparison of units. (3) The practical work in defining phraseological units and organising the phraseological zone in the Dictionary of Russian Gestures unexpectedly showed that semantic links between gestures and gestural phrasemes are reflected not only in common semantic elements and syntactic structure of semantic propositions, but also in general and partial cognitive operations that are made over semantic definitions. (4) In comparative semantic analysis one should take into account different values and roles of inner form and image components in the semantic representation of non-verbal and verbal units. (5) For the most part, gestural phrasemes are direct semantic derivatives of gestures. The cognitive and formal techniques can be regarded as typological features for the future functional-semantic classification of gestural phrasemes: two phrasemes whose meaning can be obtained by the same cognitive or purely syntactic operations (or types of operations) over the meanings of the corresponding gestures, belong by definition to one and the same class. The nature of many cognitive operations has not been studied well so far, but the first steps towards its comprehension and description have been taken. The research identified 25 logically possible classes of relationships between a gesture and a gestural phraseme. The calculation is based on theoretically possible formal (set-theory) correlations between signifiers and signified of the non-verbal and verbal units. However, in order to examine which of them are realised in practice a complete semantic and lexicographic description of all (not only central) everyday emblems and gestural phrasemes is required and this unfortunately does not yet exist. Mr. Kreidlin suggests that the results of the comparative analysis of verbal and non-verbal units could also be used in other research areas such as the lexicography of emotions.

Virtopsy - the concept of a centralized database in forensic medicine for analysis and comparison of radiological and autopsy data

Recent developments in clinical radiology have resulted in additional developments in the field of forensic radiology. After implementation of cross-sectional radiology and optical surface documentation in forensic medicine, difficulties in the validation and analysis of the acquired data was experienced. To address this problem and for the comparison of autopsy and radiological data a centralized database with internet technology for forensic cases was created. The main goals of the database are (1) creation of a digital and standardized documentation tool for forensic-radiological and pathological findings; (2) establishing a basis for validation of forensic cross-sectional radiology as a non-invasive examination method in forensic medicine that means comparing and evaluating the radiological and autopsy data and analyzing the accuracy of such data; and (3) providing a conduit for continuing research and education in forensic medicine. Considering the infrequent availability of CT or MRI for forensic institutions and the heterogeneous nature of case material in forensic medicine an evaluation of benefits and limitations of cross-sectional imaging concerning certain forensic features by a single institution may be of limited value. A centralized database permitting international forensic and cross disciplinary collaborations may provide important support for forensic-radiological casework and research.

The Virtual Skeleton Database: An Open Access Repository for Biomedical Research and Collaboration

Background: Statistical shape models are widely used in biomedical research. They are routinely implemented for automatic image segmentation or object identification in medical images. In these fields, however, the acquisition of the large training datasets, required to develop these models, is usually a time-consuming process. Even after this effort, the collections of datasets are often lost or mishandled resulting in replication of work. Objective: To solve these problems, the Virtual Skeleton Database (VSD) is proposed as a centralized storage system where the data necessary to build statistical shape models can be stored and shared. Methods: The VSD provides an online repository system tailored to the needs of the medical research community. The processing of the most common image file types, a statistical shape model framework, and an ontology-based search provide the generic tools to store, exchange, and retrieve digital medical datasets. The hosted data are accessible to the community, and collaborative research catalyzes their productivity. Results: To illustrate the need for an online repository for medical research, three exemplary projects of the VSD are presented: (1) an international collaboration to achieve improvement in cochlear surgery and implant optimization, (2) a population-based analysis of femoral fracture risk between genders, and (3) an online application developed for the evaluation and comparison of the segmentation of brain tumors. Conclusions: The VSD is a novel system for scientific collaboration for the medical image community with a data-centric concept and semantically driven search option for anatomical structures. The repository has been proven to be a useful tool for collaborative model building, as a resource for biomechanical population studies, or to enhance segmentation algorithms.

A distributed, semiotic-inductive and human-Oriented approach to web-scale knowledge retrieval

Web-scale knowledge retrieval can be enabled by distributed information retrieval, clustering Web clients to a large-scale computing infrastructure for knowledge discovery from Web documents. Based on this infrastructure, we propose to apply semiotic (i.e., sub-syntactical) and inductive (i.e., probabilistic) methods for inferring concept associations in human knowledge. These associations can be combined to form a fuzzy (i.e.,gradual) semantic net representing a map of the knowledge in the Web. Thus, we propose to provide interactive visualizations of these cognitive concept maps to end users, who can browse and search the Web in a human-oriented, visual, and associative interface.

The CoastColour Round Robin datasets: a database to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters

The CoastColour project Round Robin (CCRR) project (http://www.coastcolour.org) funded by the European Space Agency (ESA) was designed to bring together a variety of reference datasets and to use these to test algorithms and assess their accuracy for retrieving water quality parameters. This information was then developed to help end-users of remote sensing products to select the most accurate algorithms for their coastal region. To facilitate this, an inter-comparison of the performance of algorithms for the retrieval of in-water properties over coastal waters was carried out. The comparison used three types of datasets on which ocean colour algorithms were tested. The description and comparison of the three datasets are the focus of this paper, and include the Medium Resolution Imaging Spectrometer (MERIS) Level 2 match-ups, in situ reflectance measurements and data generated by a radiative transfer model (HydroLight). The datasets mainly consisted of 6,484 marine reflectance associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: Total Suspended Matter (TSM) and Chlorophyll-a (CHL) concentrations, and the absorption of Coloured Dissolved Organic Matter (CDOM). Inherent optical properties were also provided in the simulated datasets (5,000 simulations) and from 3,054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three datasets are compared. Match-up and in situ sites where deviations occur are identified. The distribution of the three reflectance datasets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.

Cloud Computing Service for Managing Large Medical Image Data-Sets Using Balanced Collaborative Agents

Managing large medical image collections is an increasingly demanding important issue in many hospitals and other medical settings. A huge amount of this information is daily generated, which requires robust and agile systems. In this paper we present a distributed multi-agent system capable of managing very large medical image datasets. In this approach, agents extract low-level information from images and store them in a data structure implemented in a relational database. The data structure can also store semantic information related to images and particular regions. A distinctive aspect of our work is that a single image can be divided so that the resultant sub-images can be stored and managed separately by different agents to improve performance in data accessing and processing. The system also offers the possibility of applying some region-based operations and filters on images, facilitating image classification. These operations can be performed directly on data structures in the database.

DAEDALUS at ImageCLEF Medical Retrieval 2011: Textual, Visual and Multimodal Experiments

This paper describes the participation of DAEDALUS at ImageCLEF 2011 Medical Retrieval task. We have focused on multimodal (or mixed) experiments that combine textual and visual retrieval. The main objective of our research has been to evaluate the effect on the medical retrieval process of the existence of an extended corpus that is annotated with the image type, associated to both the image itself and also to its textual description. For this purpose, an image classifier has been developed to tag each document with its class (1st level of the hierarchy: Radiology, Microscopy, Photograph, Graphic, Other) and subclass (2nd level: AN, CT, MR, etc.). For the textual-based experiments, several runs using different semantic expansion techniques have been performed. For the visual-based retrieval, different runs are defined by the corpus used in the retrieval process and the strategy for obtaining the class and/or subclass. The best results are achieved in runs that make use of the image subclass based on the classification of the sample images. Although different multimodal strategies have been submitted, none of them has shown to be able to provide results that are at least comparable to the ones achieved by the textual retrieval alone. We believe that we have been unable to find a metric for the assessment of the relevance of the results provided by the visual and textual processes

The Arabidopsis Information Resource (TAIR): a comprehensive database and web-based information retrieval, analysis, and visualization system for a model plant

Arabidopsis thaliana, a small annual plant belonging to the mustard family, is the subject of study by an estimated 7000 researchers around the world. In addition to the large body of genetic, physiological and biochemical data gathered for this plant, it will be the first higher plant genome to be completely sequenced, with completion expected at the end of the year 2000. The sequencing effort has been coordinated by an international collaboration, the Arabidopsis Genome Initiative (AGI). The rationale for intensive investigation of Arabidopsis is that it is an excellent model for higher plants. In order to maximize use of the knowledge gained about this plant, there is a need for a comprehensive database and information retrieval and analysis system that will provide user-friendly access to Arabidopsis information. This paper describes the initial steps we have taken toward realizing these goals in a project called The Arabidopsis Information Resource (TAIR) (www.arabidopsis.org).

Using WordNet relations and semantic classes in information retrieval tasks

In this paper we explore the use of semantic classes in an existing information retrieval system in order to improve its results. Thus, we use two different ontologies of semantic classes (WordNet domain and Basic Level Concepts) in order to re-rank the retrieved documents and obtain better recall and precision. Finally, we implement a new method for weighting the expanded terms taking into account the weights of the original query terms and their relations in WordNet with respect to the new ones (which have demonstrated to improve the results). The evaluation of these approaches was carried out in the CLEF Robust-WSD Task, obtaining an improvement of 1.8% in GMAP for the semantic classes approach and 10% in MAP employing the WordNet term weighting approach.