A Theoretical Growth Model for Ireland

Ireland is distinguished by the high degree of openness of its labour market and the importance of foreign direct investment (FDI) in the economy. We develop a neo-classical growth model to explore the consequence of these characteristics for the response of an economy to the kinds of shocks that are widely recognised to have been of importance in driving the Irish boom.

Using Sparse Semantic Embeddings Learned from Multimodal Text and Image Data to Model Human Conceptual Knowledge

Distributional models provide a convenient way to model semantics using dense embedding spaces derived from unsupervised learning algorithms. However, the dimensions of dense embedding spaces are not designed to resemble human semantic knowledge. Moreover, embeddings are often built from a single source of information (typically text data), even though neurocognitive research suggests that semantics is deeply linked to both language and perception. In this paper, we combine multimodal information from both text and image-based representations derived from state-of-the-art distributional models to produce sparse, interpretable vectors using Joint Non-Negative Sparse Embedding. Through in-depth analyses comparing these sparse models to human-derived behavioural and neuroimaging data, we demonstrate their ability to predict interpretable linguistic descriptions of human ground-truth semantic knowledge.Comment: Proceedings of the 22nd Conference on Computational Natural Language Learning (CoNLL 2018), pages 260-270. Brussels, Belgium, October 31 - November 1, 2018. Association for Computational Linguistic

Phonological and syntactic competition effects in spoken word recognition: evidence from corpus-based statistics.

This is the final version of the article. It first appeared from Taylor and Francis via https://doi.org/10.1080/23273798.2016.1241886As spoken language unfolds over time the speech input transiently activates multiple candidates at different levels of the system - phonological, lexical, and syntactic - which in turn leads to short-lived between-candidate competition. In an fMRI study, we investigated how different kinds of linguistic competition may be modulated by the presence or absence of a prior context (Tyler 1984; Tyler et al. 2008). We found significant effects of lexico-phonological competition for isolated words, but not for words in short phrases, with high competition yielding greater activation in left inferior frontal gyrus (LIFG) and posterior temporal regions. This suggests that phrasal contexts reduce lexico-phonological competition by eliminating form-class inconsistent cohort candidates. A corpus-derived measure of lexico-syntactic competition was associated with greater activation in LIFG for verbs in phrases, but not for isolated verbs, indicating that lexico-syntactic information is boosted by the phrasal context. Together, these findings indicate that LIFG plays a general role in resolving different kinds of linguistic competition.This research was funded by an EPSRC, UK, grant to Lorraine K. Tyler [grant number EP/F030061/1], and by the European Research Council under the European Commission Seventh Fra- mework Programme (FP7/2007- 2013) [grant number 249640] to Lorraine K. Tyler

Oscillatory dynamics of perceptual to conceptual transformations in the ventral visual pathway

Object recognition requires dynamic transformations of low-level visual inputs to complex semantic representations. While this process depends on the ventral visual pathway (VVP), we lack an incremental account from low-level inputs to semantic representations, and the mechanistic details of these dynamics. Here we combine computational models of vision with semantics, and test the output of the incremental model against patterns of neural oscillations recorded with MEG in humans. Representational Similarity Analysis showed visual information was represented in alpha activity throughout the VVP, and semantic information was represented in theta activity. Furthermore, informational connectivity showed visual information travels through feedforward connections, while visual information is transformed into semantic representations through feedforward and feedback activity, centered on the anterior temporal lobe. Our research highlights that the complex transformations between visual and semantic information is driven by feedforward and recurrent dynamics resulting in object-specific semantics

Representational similarity analysis reveals commonalities and differences in the semantic processing of words and objects.

Understanding the meanings of words and objects requires the activation of underlying conceptual representations. Semantic representations are often assumed to be coded such that meaning is evoked regardless of the input modality. However, the extent to which meaning is coded in modality-independent or amodal systems remains controversial. We address this issue in a human fMRI study investigating the neural processing of concepts, presented separately as written words and pictures. Activation maps for each individual word and picture were used as input for searchlight-based multivoxel pattern analyses. Representational similarity analysis was used to identify regions correlating with low-level visual models of the words and objects and the semantic category structure common to both. Common semantic category effects for both modalities were found in a left-lateralized network, including left posterior middle temporal gyrus (LpMTG), left angular gyrus, and left intraparietal sulcus (LIPS), in addition to object- and word-specific semantic processing in ventral temporal cortex and more anterior MTG, respectively. To explore differences in representational content across regions and modalities, we developed novel data-driven analyses, based on k-means clustering of searchlight dissimilarity matrices and seeded correlation analysis. These revealed subtle differences in the representations in semantic-sensitive regions, with representations in LIPS being relatively invariant to stimulus modality and representations in LpMTG being uncorrelated across modality. These results suggest that, although both LpMTG and LIPS are involved in semantic processing, only the functional role of LIPS is the same regardless of the visual input, whereas the functional role of LpMTG differs for words and objects.This work was supported by the European Research CouncilThis is the final version of an article originally published in the Journal of Neuroscience and available online at http://www.jneurosci.org/content/33/48/18906.abstract

Predicting the Time Course of Individual Objects with MEG.

To respond appropriately to objects, we must process visual inputs rapidly and assign them meaning. This involves highly dynamic, interactive neural processes through which information accumulates and cognitive operations are resolved across multiple time scales. However, there is currently no model of object recognition which provides an integrated account of how visual and semantic information emerge over time; therefore, it remains unknown how and when semantic representations are evoked from visual inputs. Here, we test whether a model of individual objects--based on combining the HMax computational model of vision with semantic-feature information--can account for and predict time-varying neural activity recorded with magnetoencephalography. We show that combining HMax and semantic properties provides a better account of neural object representations compared with the HMax alone, both through model fit and classification performance. Our results show that modeling and classifying individual objects is significantly improved by adding semantic-feature information beyond ∼200 ms. These results provide important insights into the functional properties of visual processing across time.This is the final version. It was first published by OUP in Cerebral Cortex at http://cercor.oxfordjournals.org/content/early/2014/09/09/cercor.bhu203.long

The Centre for Speech, Language and the Brain (CSLB) concept property norms.

Theories of the representation and processing of concepts have been greatly enhanced by models based on information available in semantic property norms. This information relates both to the identity of the features produced in the norms and to their statistical properties. In this article, we introduce a new and large set of property norms that are designed to be a more flexible tool to meet the demands of many different disciplines interested in conceptual knowledge representation, from cognitive psychology to computational linguistics. As well as providing all features listed by 2 or more participants, we also show the considerable linguistic variation that underlies each normalized feature label and the number of participants who generated each variant. Our norms are highly comparable with the largest extant set (McRae, Cree, Seidenberg, & McNorgan, 2005) in terms of the number and distribution of features. In addition, we show how the norms give rise to a coherent category structure. We provide these norms in the hope that the greater detail available in the Centre for Speech, Language and the Brain norms should further promote the development of models of conceptual knowledge. The norms can be downloaded at www.csl.psychol.cam.ac.uk/propertynorms

Metal complexes of 1,10-phenanthroline-5,6-dione alter the susceptibility of the yeast Candida albicans to Amphotericin B and Miconazole

Growth of the pathogenic yeast Candida albicans in sub-MIC (minimum inhibitory concentration) levels of Cu(ClO4)2 · 6H2O and [Cu(phendio)3](ClO4)2 · 4H2O (phendio = 1,10-phenanthroline-5,6-dione) increased the concentration of miconazole and amphotericin B required to achieve the MIC90 whereas pre-growth in AgClO4 and [Ag(phendio)2]ClO4 resulted in a small decrease in the relevant MIC90 values. The copper complexes reduce the oxygen consumption of C. albicans while the silver complexes increase oxygen consumption. In addition, pregrowth of cells in the copper complexes resulted in a lower ergosterol content while the silver complexes induced an elevation in ergosterol synthesis. The ability of copper and silver complexes to alter the susceptibility of C. albicans to miconazole and amphotericin B may be influenced by their action on respiration, since reduced respiration rates correlate with reduced cellular ergosterol which is the target for amphotericin B. Lower levels of ergosterol have previously been associated with elevated tolerance to this drug. In the case of reduced sensitivity to miconazole, tolerance may be mediated by lower ergosterol synthesis giving rise to fewer toxic side products once biosynthesis is inhibited by miconazole

In vitro anti-tumour effect of 1,10-phenanthroline-5,6-dione (phendione), [Cu(phendione)3](ClO4)2·4H2O and [Ag(phendione)2]ClO4 using human epithelial cell lines.

The anti-cancer chemotherapeutic potential of 1,10-phenanthroline-5,6-dione (phendione), [Cu(phendione)3](ClO4)2·4H2O and [Ag(phendione)2]ClO4 were determined using four human cells lines, i.e. two neoplastic (A-498 and Hep-G2) and two non-neoplastic (CHANG and HK-2). All of the phendione derivatives induced a concentration-dependant decrease in the viability of the four cell lines, with [Cu(phendione)3](ClO4)2·4H2O displaying greatest activity. In comparative studies, IC50 values obtained with the two neoplastic cell lines showed a cytotoxic response which was between 3 and 35 times greater than that observed for the metal-based anti-cancer agent, cisplatin. Furthermore, metal–phendione complexes, rather than simple solvated metal ions, were responsible for the observed cytotoxicity. Despite the high level of potency associated with these compounds they did not display an apparent cyto-selective profile, as they reduced the viability of both neoplastic and non-neoplastic cells. However, selected mechanistic studies showed that phendione and its metal complexes inhibited DNA synthesis which did not appear to be mediated through intercalation. Ames testing highlighted that all three compounds and their phase I metabolites were non-mutagenic, unlike cisplatin. Taken together, these results suggest that phendione and its Cu(II) and Ag(I) complexes may be capable of acting as highly effective anti-cancer therapies, which with careful administration could provide very potent and effective alternatives to cisplatin

In vitro cancer chemotherapeutic activity of 1,10-phenanthroline (phen), [Ag2(phen)3(mal)] Æ 2H2O, [Cu(phen)2(mal)] Æ 2H2O and [Mn(phen)2(mal)] Æ 2H2O (malH2 = malonic acid) using human cancer cells.

The chemotherapeutic potential of 1,10-phenanthroline (phen), and three of its transition metal complexes, namely [Cu(phen)2(mal)] Æ 2H2O, [Mn(phen)2(mal)] Æ 2H2O and [Ag2(phen)3(mal)] Æ 2H2O (malH2 = malonic acid) was determined using two human carcinoma cell lines (A-498 and Hep-G2). Phen and the three metal–phen complexes induced a concentration- dependent cytotoxic effect, with metal complexes demonstrating the greatest cytotoxic response. In comparative studies, IC50 values show cytotoxicity of between 3 and 18 times greater than that observed for the metal-based anti-cancer agent, cisplatin. All of the phen-based complexes inhibited DNA synthesis which did not appear to be mediated through intercalation. Also, the potential cancer chemotherapeutic application of these compounds was seen to be enhanced by results obtained from Ames tests, which showed all of the test agents and their phase I metabolites were non-mutagenic. Taken together, these results suggest that phen and the three metal–phen complexes may have a therapeutic role to play in the successful treatment and management of cancer