Does normal processing provide evidence of specialised semantic subsystems?

Category-specific disorders are frequently explained by suggesting that living and non-living things are processed in separate subsystems (e.g. Caramazza & Shelton, 1998). If subsystems exist, there should be benefits for normal processing, beyond the influence of structural similarity. However, no previous study has separated the relative influences of similarity and semantic category. We created novel examples of living and non-living things so category and similarity could be manipulated independently. Pre-tests ensured that our images evoked appropriate semantic information and were matched for familiarity. Participants were trained to associate names with the images and then performed a name-verification task under two levels of time pressure. We found no significant advantage for living things alongside strong effects of similarity. Our results suggest that similarity rather than category is the key determinant of speed and accuracy in normal semantic processing. We discuss the implications of this finding for neuropsychological studies. © 2005 Psychology Press Ltd.

Combining temporal and spectral information with spatial mapping to identify differences between phonological and semantic networks:a magnetoencephalographic approach

Early, lesion-based models of language processing suggested that semantic and phonological processes are associated with distinct temporal and parietal regions respectively, with frontal areas more indirectly involved. Contemporary spatial brain mapping techniques have not supported such clear-cut segregation, with strong evidence of activation in left temporal areas by both processes and disputed evidence of involvement of frontal areas in both processes. We suggest that combining spatial information with temporal and spectral data may allow a closer scrutiny of the differential involvement of closely overlapping cortical areas in language processing. Using beamforming techniques to analyze magnetoencephalography data, we localized the neuronal substrates underlying primed responses to nouns requiring either phonological or semantic processing, and examined the associated measures of time and frequency in those areas where activation was common to both tasks. Power changes in the beta (14-30 Hz) and gamma (30-50 Hz) frequency bandswere analyzed in pre-selected time windows of 350-550 and 500-700ms In left temporal regions, both tasks elicited power changes in the same time window (350-550 ms), but with different spectral characteristics, low beta (14-20 Hz) for the phonological task and high beta (20-30 Hz) for the semantic task. In frontal areas (BA10), both tasks elicited power changes in the gamma band (30-50 Hz), but in different time windows, 500-700ms for the phonological task and 350-550ms for the semantic task. In the left inferior parietal area (BA40), both tasks elicited changes in the 20-30 Hz beta frequency band but in different time windows, 350-550ms for the phonological task and 500-700ms for the semantic task. Our findings suggest that, where spatial measures may indicate overlapping areas of involvement, additional beamforming techniques can demonstrate differential activation in time and frequency domains. © 2012 McNab, Hillebrand, Swithenby and Rippon.

The development of a semantic model for the interpretation of mathematics including the use of technology

The semantic model developed in this research was in response to the difficulty a group of mathematics learners had with conventional mathematical language and their interpretation of mathematical constructs. In order to develop the model ideas from linguistics, psycholinguistics, cognitive psychology, formal languages and natural language processing were investigated. This investigation led to the identification of four main processes: the parsing process, syntactic processing, semantic processing and conceptual processing. The model showed the complex interdependency between these four processes and provided a theoretical framework in which the behaviour of the mathematics learner could be analysed. The model was then extended to include the use of technological artefacts into the learning process. To facilitate this aspect of the research, the theory of instrumentation was incorporated into the semantic model. The conclusion of this research was that although the cognitive processes were interdependent, they could develop at different rates until mastery of a topic was achieved. It also found that the introduction of a technological artefact into the learning environment introduced another layer of complexity, both in terms of the learning process and the underlying relationship between the four cognitive processes.

Investigation of the neural correlates of recognition memory using magnetoencephalography

Neuroimaging literature has identified several regions involved in encoding and recognition processes. A review of the literature illustrated considerable variations in the precise location and mechanisms of these processes, and it was these variations that were investigated in the studies in this thesis. Magnetoencephalography (MEG) was used as the neuroimaging tool and a preliminary study identified Synthetic Aperture Magnetometry (SAM) and not a traditional dipole fitting technique, as an appropriate tool for identifying the multiple cortical regions involved in recognition memory. It has been suggested that there is hemispheric asymmetry in encoding and recognition processes. There are two main hypotheses: the first suggesting that there is task-specificity, the second that this specificity is determined by stimulus modality. A series of experiments was completed with two main aims: first to produce consistent and complementary recognition memory data with MEG, and second to determine whether there exists any hemispheric asymmetry in recognition memory. The results obtained from five experiments demonstrated activation of prefrontal and middle temporal structures, which were consistent with those reported in previous neuroimaging studies. It was suggested that this diverse activation may be explained by the involvement of a semantic network during recognition memory processes. In support of this, a subsequent study involving a semantic encoding task demonstrated that category-specific differences in cortical activation also existed in the recognition memory phase. Controlling for the involvement of such semantic processes produced predominantly bilateral activation. It was suggested that the apparent hemispheric asymmetry findings reported in the literature may be due to the 'coarse' temporal analysis available with earlier imaging techniques, which over-simplified the networks reported by being unable to recognise the early complex processes associated with semantic processing which these MEG studies were able to identify. The importance of frequency-specific activations, specifically theta synchronisation and alpha desynchronisation, in memory processes was also investigated.

Pediatric CNS pathophysiology

Research in pediatric central nervous system pathophysiology is focused around three primary goals: identification of neurodevelopmental disorders, understanding the differences in brain development which underlie these disorders, and improving treatment for these young children. Autism spectrum disorders (ASDs) are a complex set of disorders which are characterized by difficulties in language and social interactions. These behavioral measures are highly variable and a number of underlying causes can generate similar behavioral effects. Therefore, it is important to identify neurophysiological markers to better identify and characterize these disorders. Recent ASD findings using MEG show atypical latency and amplitude responses and poor cortical connectivity in children with ASDs across the cognitive spectrum from basic auditory processing, multisensory integration, to face and semantic processing. These results further support the view that ASDs are a complex neurologically-based disorder. On the other hand, the cause of Down syndrome is well understood as originating from a partial or full replication of chromosome 21. However, the cognitive and neurological consequences of this chromosomal abnormality are not yet well understood. Using a simple observation and motor execution task, poor functional connectivity in sensory-motor areas, particularly in the gamma band range, has been identified in children with Down syndrome and is consistent with behavioral deficits in the sensory-motor realm. Additional studies are needed to better understand whether targeted identification of these abnormalities can facilitate treatment in this disorder. Finally, while epilepsy can be reliably diagnosed, seizure control is still limited in many cases where the seizure onset zone is not readily apparent. Advances in pre-surgical evaluation and intra-operative co-registration will be described. These studies describing pediatric CNS pathophysiology will be discussed. © Springer-Verlag 2010.

Natural language processing as a foundation of the semantic Web

The main argument of this paper is that Natural Language Processing (NLP) does, and will continue to, underlie the Semantic Web (SW), including its initial construction from unstructured sources like the World Wide Web (WWW), whether its advocates realise this or not. Chiefly, we argue, such NLP activity is the only way up to a defensible notion of meaning at conceptual levels (in the original SW diagram) based on lower level empirical computations over usage. Our aim is definitely not to claim logic-bad, NLP-good in any simple-minded way, but to argue that the SW will be a fascinating interaction of these two methodologies, again like the WWW (which has been basically a field for statistical NLP research) but with deeper content. Only NLP technologies (and chiefly information extraction) will be able to provide the requisite RDF knowledge stores for the SW from existing unstructured text databases in the WWW, and in the vast quantities needed. There is no alternative at this point, since a wholly or mostly hand-crafted SW is also unthinkable, as is a SW built from scratch and without reference to the WWW. We also assume that, whatever the limitations on current SW representational power we have drawn attention to here, the SW will continue to grow in a distributed manner so as to serve the needs of scientists, even if it is not perfect. The WWW has already shown how an imperfect artefact can become indispensable.

A systematic exploration of perceptual and semantic differences in category-specific object-processing using magnetoencephalography

In a series of experiments, we tested category-specific activation in normal parti¬cipants using magnetoencephalography (MEG). Our experiments explored the temporal processing of objects, as MEG characterises neural activity on the order of milliseconds. Our experiments explored object-processing, including assessing the time-course of ob¬ject naming, early differences in processing living compared with nonliving objects and processing objects at the basic compared with the domain level, and late differences in processing living compared with nonliving objects and processing objects at the basic compared with the domain level. In addition to studies using normal participants, we also utilised MEG to explore category-specific processing in a patient with a deficit for living objects. Our findings support the cascade model of object naming (Humphreys et al., 1988). In addition, our findings using normal participants demonstrate early, category-specific perceptual differences. These findings are corroborated by our patient study. In our assessment of the time-course of category-specific effects as well as a separate analysis designed to measure semantic differences between living and nonliving objects, we found support for the sensory/motor model of object naming (Martin, 1998), in addition to support for the cascade model of object naming. Thus, object processing in normal participants appears to be served by a distributed network in the brain, and there are both perceptual and semantic differences between living and nonliving objects. A separate study assessing the influence of the level at which you are asked to identify an object on processing in the brain found evidence supporting the convergence zone hypothesis (Damasio, 1989). Taken together, these findings indicate the utility of MEG in exploring the time-course of object processing, isolating early perceptual and later semantic effects within the brain.

Spatially structured cognitve models of semantic information:the implications for computerised databases

Existing theories of semantic cognition propose models of cognitive processing occurring in a conceptual space, where ‘meaning’ is derived from the spatial relationships between concepts’ mapped locations within the space. Information visualisation is a growing area of research within the field of information retrieval, and methods for presenting database contents visually in the form of spatial data management systems (SDMSs) are being developed. This thesis combined these two areas of research to investigate the benefits associated with employing spatial-semantic mapping (documents represented as objects in two- and three-dimensional virtual environments are proximally mapped dependent on the semantic similarity of their content) as a tool for improving retrieval performance and navigational efficiency when browsing for information within such systems. Positive effects associated with the quality of document mapping were observed; improved retrieval performance and browsing behaviour were witnessed when mapping was optimal. It was also shown using a third dimension for virtual environment (VE) presentation provides sufficient additional information regarding the semantic structure of the environment that performance is increased in comparison to using two-dimensions for mapping. A model that describes the relationship between retrieval performance and browsing behaviour was proposed on the basis of findings. Individual differences were not found to have any observable influence on retrieval performance or browsing behaviour when mapping quality was good. The findings from this work have implications for both cognitive modelling of semantic information, and for designing and testing information visualisation systems. These implications are discussed in the conclusions of this work.

The functional organisation of the fronto-temporal language system:evidence from syntactic and semantic ambiguity

Spoken language comprehension is known to involve a large left-dominant network of fronto-temporal brain regions, but there is still little consensus about how the syntactic and semantic aspects of language are processed within this network. In an fMRI study, volunteers heard spoken sentences that contained either syntactic or semantic ambiguities as well as carefully matched low-ambiguity sentences. Results showed ambiguity-related responses in the posterior left inferior frontal gyrus (pLIFG) and posterior left middle temporal regions. The pLIFG activations were present for both syntactic and semantic ambiguities suggesting that this region is not specialised for processing either semantic or syntactic information, but instead performs cognitive operations that are required to resolve different types of ambiguity irrespective of their linguistic nature, for example by selecting between possible interpretations or reinterpreting misparsed sentences. Syntactic ambiguities also produced activation in the posterior middle temporal gyrus. These data confirm the functional relationship between these two brain regions and their importance in constructing grammatical representations of spoken language.

Describing and communicating uncertainty within the semantic web

The Semantic Web relies on carefully structured, well defined, data to allow machines to communicate and understand one another. In many domains (e.g. geospatial) the data being described contains some uncertainty, often due to incomplete knowledge; meaningful processing of this data requires these uncertainties to be carefully analysed and integrated into the process chain. Currently, within the SemanticWeb there is no standard mechanism for interoperable description and exchange of uncertain information, which renders the automated processing of such information implausible, particularly where error must be considered and captured as it propagates through a processing sequence. In particular we adopt a Bayesian perspective and focus on the case where the inputs / outputs are naturally treated as random variables. This paper discusses a solution to the problem in the form of the Uncertainty Markup Language (UncertML). UncertML is a conceptual model, realised as an XML schema, that allows uncertainty to be quantified in a variety of ways i.e. realisations, statistics and probability distributions. UncertML is based upon a soft-typed XML schema design that provides a generic framework from which any statistic or distribution may be created. Making extensive use of Geography Markup Language (GML) dictionaries, UncertML provides a collection of definitions for common uncertainty types. Containing both written descriptions and mathematical functions, encoded as MathML, the definitions within these dictionaries provide a robust mechanism for defining any statistic or distribution and can be easily extended. Universal Resource Identifiers (URIs) are used to introduce semantics to the soft-typed elements by linking to these dictionary definitions. The INTAMAP (INTeroperability and Automated MAPping) project provides a use case for UncertML. This paper demonstrates how observation errors can be quantified using UncertML and wrapped within an Observations & Measurements (O&M) Observation. The interpolation service uses the information within these observations to influence the prediction outcome. The output uncertainties may be encoded in a variety of UncertML types, e.g. a series of marginal Gaussian distributions, a set of statistics, such as the first three marginal moments, or a set of realisations from a Monte Carlo treatment. Quantifying and propagating uncertainty in this way allows such interpolation results to be consumed by other services. This could form part of a risk management chain or a decision support system, and ultimately paves the way for complex data processing chains in the Semantic Web.

Automatically Extracting Procedural Knowledge from Instructional Texts using Natural Language Processing

Procedural knowledge is the knowledge required to perform certain tasks, and forms an important part of expertise. A major source of procedural knowledge is natural language instructions. While these readable instructions have been useful learning resources for human, they are not interpretable by machines. Automatically acquiring procedural knowledge in machine interpretable formats from instructions has become an increasingly popular research topic due to their potential applications in process automation. However, it has been insufficiently addressed. This paper presents an approach and an implemented system to assist users to automatically acquire procedural knowledge in structured forms from instructions. We introduce a generic semantic representation of procedures for analysing instructions, using which natural language techniques are applied to automatically extract structured procedures from instructions. The method is evaluated in three domains to justify the generality of the proposed semantic representation as well as the effectiveness of the implemented automatic system.