Behavioural and neuropsychological evidence suggests that abstract and concrete concepts might be represented, retrieved and processed differently in the human brain. Using fMRI, we demonstrate that retrieval of abstract relative to sensory-based semantics during synonym judgements increased activation in a left frontotemporal system that has been associated with semantic processing particularly at the sentence level. Since activation increases were observed irrespective of the degree of difficulty, we suggest that these differential activations might reflect a particular retrieval mechanism or strategy for abstract concepts. In contrast to sensory-based semantics, the meaning of abstract concepts is largely specified by their usage in language rather than by their relations to the physical world. Subjects might therefore generate an appropriate semantic sentential context to fully explore and specify the meaning of abstract concepts. Our results also explain why abstract semantics is vulnerable to left frontotemporal lesions.

The development of e-Science presents a major set of opportunities and challenges for the future progress of biological and life scientific research. Major new tools are required and corresponding demands are placed on the high-throughput data generated and used in these processes. Nowhere is the demand greater than in the semantic integration of these data. Semantic Web tools and technologies afford the chance to achieve this semantic integration. Since pathway knowledge is central to much of the scientific research today it is a good test-bed for semantic integration. Within the context of biological pathways, the BioPAX initiative, part of a broader movement towards the standardization and integration of life science databases, forms a necessary prerequisite for its successful application of e-Science in health care and life science research. This paper examines whether BioPAX, an effort to overcome the barrier of disparate and heterogeneous pathway data sources, addresses the needs of e-Science.

The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility. To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously 'unseen' (not used for the construction of EXACT2)protocols.

There is ongoing debate on whether object meaning can be processed outside foveal vision, making semantics available for attentional guidance. Much of the debate has centred on whether objects that do not fit within an overall scene draw attention, in complex displays that are often difficult to control. Here, we revisited the question by reanalysing data from three experiments that used displays consisting of standalone objects from a carefully controlled stimulus set. Observers searched for a target object, as per auditory instruction. On the critical trials, the displays contained no target but objects that were semantically related to the target, visually related, or unrelated. Analyses using (generalized) linear mixed-effects models showed that, although visually related objects attracted most attention, semantically related objects were also fixated earlier in time than unrelated objects. Moreover, semantic matches affected the very first saccade in the display. The amplitudes of saccades that first entered semantically related objects were larger than 5° on average, confirming that object semantics is available outside foveal vision. Finally, there was no semantic capture of attention for the same objects when observers did not actively look for the target, confirming that it was not stimulus-driven. We discuss the implications for existing models of visual cognition.

A significant portion of biomedical literature is represented in a manner that makes it difficult for consumers to find or aggregate content through a computational query. One approach to facilitate reuse of the scientific literature is to structure this information as linked data using standardized web technologies. In this paper we present the second version of Biotea, a semantic, linked data version of the open-access subset of PubMed Central that has been enhanced with specialized annotation pipelines that uses existing infrastructure from the National Center for Biomedical Ontology. We expose our models, services, software and datasets. Our infrastructure enables manual and semi-automatic annotation, resulting data are represented as RDF-based linked data and can be readily queried using the SPARQL query language. We illustrate the utility of our system with several use cases. Our datasets, methods and techniques are available at http://biotea.github.io.

Several studies have recently shown that basal ganglia (BG) deterioration leads to distinctive impairments in the domains of syntax, action verbs, and action semantics. In particular, such disruptions have been repeatedly observed in Parkinson's disease (PD) patients. However, it remains unclear whether these deficits are language-specific and whether they are equally dissociable from other reported disturbances -viz., processing of object semantics. To address these issues, we administered linguistic, semantic, and executive function (EFs) tasks to two groups of non-demented PD patients, with and without mild cognitive impairment (PD-MCI and PD-nMCI, respectively). We compared these two groups with each other and with matched samples of healthy controls. Our results showed that PD patients exhibited linguistic and semantic deficits even in the absence of MCI. However, not all domains were equally related to EFs and MCI across samples. Whereas EFs predicted disturbances of syntax and object semantics in both PD-nMCI and PD-MCI, they had no impact on action-verb and action-semantic impairments in either group. Critically, patients showed disruptions of action-verb production and action semantics in the absence of MCI and without any executive influence, suggesting a sui generis deficit present since early stages of the disease. These findings indicate that varied language domains are differentially related to the BG, contradicting popular approaches to neurolinguistics.

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.

An experimental protocol is a sequence of tasks and operations executed to perform experimental research in biological and biomedical areas, e.g. biology, genetics, immunology, neurosciences, virology. Protocols often include references to equipment, reagents, descriptions of critical steps, troubleshooting and tips, as well as any other information that researchers deem important for facilitating the reusability of the protocol. Although experimental protocols are central to reproducibility, the descriptions are often cursory. There is the need for a unified framework with respect to the syntactic structure and the semantics for representing experimental protocols.

Personality assessment and, specifically, the assessment of personality disorders have traditionally been indifferent to computational models. Computational personality is a new field that involves the automatic classification of individuals' personality traits that can be compared against gold-standard labels. In this context, we introduce a new vectorial semantics approach to personality assessment, which involves the construction of vectors representing personality dimensions and disorders, and the automatic measurements of the similarity between these vectors and texts written by human subjects. We evaluated our approach by using a corpus of 2468 essays written by students who were also assessed through the five-factor personality model. To validate our approach, we measured the similarity between the essays and the personality vectors to produce personality disorder scores. These scores and their correspondence with the subjects' classification of the five personality factors reproduce patterns well-documented in the psychological literature. In addition, we show that, based on the personality vectors, we can predict each of the five personality factors with high accuracy.

Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies are well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. In this manuscript, we present (1) use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2) two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3) two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE) and the Biological Collections Ontology (BCO); these provide a starting point for the development of a data model linking phenotypes and environments.

Progress on research and innovation in food technology depends increasingly on the use of structured vocabularies-concept schemes, thesauri, and ontologies-for discovering and re-using a diversity of data sources. Here, we report on GACS Core, a concept scheme in the larger Global Agricultural Concept Space (GACS), which was formed by mapping between the most frequently used concepts of AGROVOC, CAB Thesaurus, and NAL Thesaurus and serves as a target for mapping near-equivalent concepts from other vocabularies. It provides globally unique identifiers, which can be used as keywords in bibliographic databases, tags for web content, for building lightweight facet schemes, and for annotating spreadsheets, databases, and image metadata using synonyms and variant labels in 25 languages. The minimal semantics of GACS allows terms defined with more precision in ontologies, or less precision in controlled vocabularies, to be linked together making it easier to discover and integrate semantically diverse data sources.

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments.

Although the CIS countries are connected together by the legacy of breaking away from the Soviet Union, they have had a distinctive transition course and are rather diverse in terms of the population ageing challenges and policy responses in place. The commonality is that a comprehensive national strategy on ageing is lacking, and many of necessary reforms were put aside owing to political uncertainties, lack of societal consensus, and financial instability. The notion of active ageing is associated with the term "accelerated ageing," which is understood to be an individual living a life under harsh living conditions or a society experiencing rapid increases in the relative number of older persons, and therefore it carries a negative connotation. Yet, in the same spirit as the European Year for Active Ageing and Solidarity between Generations 2012, the CIS countries have initiated sectoral programmes towards enhancing employment of older workers, social participation of older people in the society in a wider sense and also measures promoting health and independent living of older persons.

The manual processes used for risk assessments are not scaling to the amount of data available. Although automated approaches appear promising, they must be transparent in a public policy setting.

An essential computational component of the human language faculty is syntax as it regulates how words are combined into sentences. Although its neuroanatomical basis is well-specified in adults, its emergence in the maturing brain is not yet understood. Using event-related functional magnetic resonance imaging (fMRI) in a cross-sectional design, we discovered, that in contrast to what is known about adults 3-to-4- and 6-to-7-year-old children do not process syntax independently from semantics at the neural level already before these two types of information are integrated for the interpretation of a sentence. It is not until the end of the 10th year of life that children show a neural selectivity for syntax, segregated and gradually independent from semantics, in the left inferior frontal cortex as in the adult brain. Our results indicate that it takes until early adolescence for the domain-specific selectivity of syntax within the language network to develop.

The deep convolutional neural network has led the trend of vision-based road detection, however, obtaining a full road area despite the occlusion from monocular vision remains challenging due to the dynamic scenes in autonomous driving. Inferring the occluded road area requires a comprehensive understanding of the geometry and the semantics of the visible scene. To this end, we create a small but effective dataset based on the KITTI dataset named KITTI-OFRS (KITTI-occlusion-free road segmentation) dataset and propose a lightweight and efficient, fully convolutional neural network called OFRSNet (occlusion-free road segmentation network) that learns to predict occluded portions of the road in the semantic domain by looking around foreground objects and visible road layout. In particular, the global context module is used to build up the down-sampling and joint context up-sampling block in our network, which promotes the performance of the network. Moreover, a spatially-weighted cross-entropy loss is designed to significantly increases the accuracy of this task. Extensive experiments on different datasets verify the effectiveness of the proposed approach, and comparisons with current excellent methods show that the proposed method outperforms the baseline models by obtaining a better trade-off between accuracy and runtime, which makes our approach is able to be applied to autonomous vehicles in real-time.

The dynamic relationship between the neural representation of action word semantics and specific sensorimotor experience remains controversial. Here, we temporarily altered human subjects' sensorimotor experience in a 15-day head-down tilt bed rest setting, a ground-based analog of microgravity that disproportionally affects sensorimotor experiences of the lower limbs, and examined whether such effector-dependent activity deprivation specifically affected the neural processes of comprehending verbs of lower-limb actions (e.g. to kick) relative to upper-limb ones (e.g. to pinch). Using functional magnetic resonance imaging, we compared the multivoxel neural patterns for such action words prior to and after bed rest. We found an effector-specific (lower vs. upper limb) experience modulation in subcortical sensorimotor-related and anterior temporal regions. The neural action semantic representations in other effector-specific verb semantic regions (e.g. left lateral posterior temporal cortex) and motor execution regions were robust against such experience alterations. These effector-specific, sensorimotor-experience-sensitive and experience-independent patterns of verb neural representation highlight the multidimensional and dynamic nature of semantic neural representation, and the broad influence of microgravity (hence gravity) environment on cognition.

Reading is an essential part of contemporary society, yet much is still unknown about the physiological underpinnings of its information processing components. Two influential cognitive models of reading, the connectionist and dual-route cascaded models, offer very different accounts, yet evidence for one or the other remains equivocal. These models differ in several ways, including the role of semantics (word meaning) in mapping spelling to sound. We used a new effective connectivity algorithm, IMaGES, to provide a network-level perspective on these network-level models. Left hemisphere regions of interest were defined based on main effects in functional magnetic resonance imaging and included two regions linked with semantic processing-angular gyrus (AG) and inferior temporal sulcus (ITS)-and two regions linked with phonological processing-posterior superior temporal gyrus (pSTG) and posterior middle temporal gyrus (pMTG). Participants read aloud words of high or low spelling-sound consistency, word frequency, and imageability. Only the connectionist model predicted increased contributions from semantic areas with those computing phonology for low-consistency words. Effective connectivity analyses revealed that areas supporting semantic processing (e.g., the ITS) interacted with phonological areas (e.g., the pSTG), with the pattern changing as a function of word properties. Connectivity from semantic to phonological areas emerged for high- compared to low-imageability words, and a similar pattern emerged for low-consistency words, though only under certain conditions. Analyses of individual differences also showed that variation in the strength of modulation of ITS by AG was associated with reading aloud performance. Overall, these results suggest that connections with semantic processing areas are not only associated with reading aloud, but that these connections are also associated with optimal reading performance.

The anterior temporal lobe (ATL) is considered a crucial area for the representation of transmodal concepts. Recent evidence suggests that specific regions within the ATL support the representation of individual object concepts, as shown by studies combining multivariate analysis methods and explicit measures of semantic knowledge. This research looks to further our understanding by probing conceptual representations at a spatially and temporally resolved neural scale. Representational similarity analysis was applied to human intracranial recordings from anatomically defined lateral to medial ATL sub-regions. Neural similarity patterns were tested against semantic similarity measures, where semantic similarity was defined by a hybrid corpus-based and feature-based approach. Analyses show that the perirhinal cortex, in the medial ATL, significantly related to semantic effects around 200 to 400 ms, and were greater than more lateral ATL regions. Further, semantic effects were present in low frequency (theta and alpha) oscillatory phase signals. These results provide converging support that more medial regions of the ATL support the representation of basic-level visual object concepts within the first 400 ms, and provide a bridge between prior fMRI and MEG work by offering detailed evidence for the presence of conceptual representations within the ATL.

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.