Syntactic and semantic specialization in 9- to 10-year-old children during auditory sentence processing

Previous studies have found specialized syntactic and semantic processes in the adult brain during language comprehension. Young children have sophisticated semantic and syntactic aspects of language, yet many previous fMRI studies failed to detect this specialization, possibly due to experimental design and analytical methods. In this current study, 5- to 6-year-old children completed a syntactic task and a semantic task to dissociate these two processes. Multivoxel pattern analysis was used to examine the correlation of patterns within a task (between runs) or across tasks. We found that the left middle temporal gyrus showed more similar patterns within the semantic task compared with across tasks, whereas there was no difference in the correlation within the syntactic task compared with across tasks, suggesting its specialization in semantic processing. Moreover, the left superior temporal gyrus showed more similar patterns within both the semantic task and the syntactic task as compared with across tasks, suggesting its role in integration of semantic and syntactic information. In contrast to the temporal lobe, we did not find specialization or integration effects in either the opercular or triangular part of the inferior frontal gyrus. Overall, our study showed that 5- to 6-year-old children have already developed specialization and integration in the temporal lobe, but not in the frontal lobe, consistent with developmental neurocognitive models of language comprehension in typically developing young children.

Brain structural abnormalities and trait impulsivity in suicidal and non-suicidal patients with bipolar disorder

Semantic information and syntactic information are two essential dimensions of language. In recent years, most researches focus on extracting semantic information or how to extract useful information from syntactic dependency tree. As the semantic representations are closely related to syntactic ones, how to effectively integrate semantic and syntactic information is still a subject worth studying. We propose attention mechanism based on graph convolutional networks. The model integrates syntactic dependence information into semantic features and automatically achieve a balance between semantic information and syntactic information. We conducted experiments on the task of sentence-level relation extraction, and the results show that our model performs better than some previous methods.

Comparison of brain function between children and adults with autism provides an understanding of the effects of the disorder and associated maturational differences on language processing. Functional imaging (functional magnetic resonance imaging) was used to examine brain activation and cortical synchronization during the processing of literal and ironic texts in 15 children with autism, 14 children with typical development, 13 adults with autism, and 12 adult controls. Both the children and adults with autism had lower functional connectivity (synchronization of brain activity among activated areas) than their age and ability comparison group in the left hemisphere language network during irony processing, and neither autism group had an increase in functional connectivity in response to increased task demands. Activation differences for the literal and irony conditions occurred in key language-processing regions (left middle temporal, left pars triangularis, left pars opercularis, left medial frontal, and right middle temporal). The children and adults with autism differed from each other in the use of some brain regions during the irony task, with the adults with autism having activation levels similar to those of the control groups. Overall, the children and adults with autism differed from the adult and child controls in (a) the degree of network coordination, (b) the distribution of the workload among member nodes, and (3) the dynamic recruitment of regions in response to text content. Moreover, the differences between the two autism age groups may be indicative of positive changes in the neural function related to language processing associated with maturation and/or educational experience.

Previous voxel-based morphometry (VBM) and cortical thickness (CT) studies on Parkinson's disease (PD) have mainly reported the gray matter size reduction, whereas the shape of cortical surface can also change in PD patients. For the first time, we analyzed sulcal depth (SD) patterns in PD patients by using whole brain region of interest (ROI)-based approach. In a cross-sectional study, high-resolution brain structural MRI images were collected from 60 PD patients without dementia and 56 age-and sex-matched healthy controls (HC). SD and CT were estimated using the Computational Anatomy Toolbox (CAT12) and statistically compared between groups on whole brain ROI-based level using statistical parametric mapping 12 (SPM12). Additionally, correlations between regional brain changes and clinical variables were also examined. Compared to HC, PD patients showed lower SD in widespread regions, including temporal (the bilateral transverse temporal, the left inferior temporal, the right middle temporal and the right superior temporal), insular (the left insula), frontal (the left pars triangularis, the left pars opercularis and the left precentral), parietal (the bilateral superior parietal) and occipital (the right cuneus) regions. For CT, only the left pars opercularis showed lower CT in PD patients compared to HC. No regions showed higher SD or CT in PD patients compared to HC. In PD patients, a significant positive correlation was found between SD of the left pars opercularis and MMSE scores, such that lower MMSE scores were related to lower SD of the left pars opercularis. Our results of widespread lower SD, but relatively localized lower CT, indicate that SD seems to be more sensitive to brain changes than CT and may be mainly affected by white matter damage. Hence, SD may be a more promising indicator to investigate the surface shape changes in PD patients. The significant positive correlation between SD of the left pars opercularis and MMSE scores suggests that SD may be prognostic of future cognitive decline.

Anatomic, clinical, and neuropsychological correlates of spelling errors in primary progressive aphasia

ABSTRACTThe ability to integrate semantic information into the context of a sentence is essential for human communication. Several studies have shown that the predictability of a final keyword based on the sentence context influences semantic integration on the behavioral, neurophysiological, and neural level. However, the architecture of the underlying network interactions for semantic integration across the lifespan remains unclear. In this study, 32 healthy participants (30–75 years) performed an auditory cloze probability task during functional magnetic resonance imaging (fMRI), requiring lexical decisions on the sentence's final words. Semantic integration demands were implicitly modulated by presenting sentences with expected, unexpected, anomalous, or pseudoword endings. To elucidate network interactions supporting semantic integration, we combined univariate task‐based fMRI analyses with seed‐based connectivity and between‐network connectivity analyses. Behavioral data revealed typical semantic integration effects, with increased integration demands being associated with longer response latencies and reduced accuracy. Univariate results demonstrated increased left frontal and temporal brain activity for sentences with higher integration demands. Between‐network interactions highlighted the role of task‐positive and default mode networks for sentence processing with increased semantic integration demands. Furthermore, increasing integration demands led to a higher number of behaviorally relevant network interactions, suggesting that the increased between‐network coupling becomes more relevant for successful task performance as integration demands increase. Our findings elucidate the complex network interactions underlying semantic integration across the aging continuum. Stronger interactions between various task‐positive and default mode networks correlated with more efficient processing of sentences with increased semantic integration demands. These results may inform future studies with healthy old and clinical populations.

ALSC (Aspect-level Sentiment Classification) is a fine-grained task in the field of NLP (Natural Language Processing) which aims to identify the sentiment toward a given aspect. In addition to exploiting the sentence semantics and syntax, current ALSC methods focus on introducing external knowledge as a supplementary to the sentence information. However, the integration of the three categories of information is still challenging. In this paper, a novel method is devised to effectively combine sufficient semantic and syntactic information as well as use of external knowledge. The proposed model contains a sentence encoder, a semantic learning module, a syntax learning module, a knowledge enhancement module, an information fusion module and a sentiment classifier. The semantic information and syntactic information are respectively extracted via a self-attention network and a graphical convolutional network. Specifically, the KGE (Knowledge Graph Embedding) is employed to enhance the feature representation of the aspect. Then, the attention-based gate mechanism is taken to fuse three types of information. We evaluated the proposed model on three benchmark datasets and the experimental results establish strong evidence of high accuracy.

A Three-Level Information Architecture containing Syntactic Information, Semantic Information and Pragmatic Information is put forward in Comprehensive Information Theory (CIT). From this point of view, spatial data analysis is in cooperation with semantic information and Spatial Data Preprocessing (SDP) is corresponding to syntactic information. However, in many practical applications, SDP based only on syntactic information can not get a good effect. Semantics-based preprocessing may be an effective scheme. RS images mosaic is a typical SDP where optimal mosaic line extraction is the crux. Lots of researches based on syntactic information are effective just for orthophoto maps. In this paper, an overall optimal mosaic line extraction scheme has been addressed for non-Ortho RS images. It is argued that there is no projection error in the projection datum fitted by Ground Control Points (GCPs), or regional main height surface which can be recognized in medium resolution RS images. Based on above reasons, the method suggests that GCPs collecting for precise geometrical correction should be on the main height surface, as well as the mosaic line extracting for RS images mosaic. Three sheets of CBERS CCD images of Taiyuan are taken as the experimental data. According to the afore-mentioned method, by collecting GCPs in wide riverbeds, all three sheets are rectified to an existing ETM+ mosaic image. And then, the central lines of wide riverbeds in the overlapping areas are extracted as the mosaic line. The experimental result indicates that this method can extract an overall optimal mosaic line and eliminate the visual texture seam-line effectively, even for non-Ortho RS images. It concludes that SDP based on semantic information can play a good role in spatial data applications.

Classical models of language localize speech perception in the left superior temporal and production in the inferior frontal cortex. Nonetheless, neuropsychological, structural and functional studies have questioned such subdivision, suggesting an interwoven organization of the speech function within these cortices. We tested whether sub-regions within frontal and temporal speech-related areas retain specific phonological representations during both perception and production. Using functional magnetic resonance imaging and multivoxel pattern analysis, we showed functional and spatial segregation across the left fronto-temporal cortex during listening, imagery and production of vowels. In accordance with classical models of language and evidence from functional studies, the inferior frontal and superior temporal cortices discriminated among perceived and produced vowels respectively, also engaging in the non-classical, alternative function – i.e. perception in the inferior frontal and production in the superior temporal cortex. Crucially, though, contiguous and non-overlapping sub-regions within these hubs performed either the classical or non-classical function, the latter also representing non-linguistic sounds (i.e., pure tones). Extending previous results and in line with integration theories, our findings not only demonstrate that sensitivity to speech listening exists in production-related regions and vice versa, but they also suggest that the nature of such interwoven organisation is built upon low-level perception.

Chapter 4 - The Contribution of Human Superior Intraparietal Sulcus to Visual Short-Term Memory and Perception

Prediction of subsequent recognition performance using brain activity in the medial temporal lobe

Event Abstract Back to Event Age of acquisition of the second language modulates structural and functional dynamics of bilingual reading Myriam Oliver1*, Manuel Carreiras1, Yasser Iturria Medina2 and Pedro M. Paz-Alonso1 1 Basque Center on Cognition,Brain and Language, Spain 2 Montreal Neurological Institute, Canada Neuroimaging evidence has suggested the involvement of left-lateralized perisylvian regions in reading processes (Turkeltaub et al., 2002). In contrast, research on bilingualism has showed contradictory evidence in regard to the differential involvement of language-related brain regions and networks for reading in the native (L1) and second language (L2) (Hernandez et al., 2015). This highlights the relevance of investigating in a systematic manner the main factors modulating the differential involvement of reading regions and networks in bilinguals, while controlling other potential sources of variance. The age-of-acquisition(AoA) of the L2 and language proficiency have been pointed out as critical variables that can determine potential differences in brain function and structure among bilingual readers (Klein et al., 2014). Here, we sought to investigate the effects of the L2 AoA on the function and structure of language-related regions associated with L1 and L2 reading, while controlling language proficiency and exposition to L1 and L2. To this end, we followed a multimodal neuroimaging approach examining fMRI, cortical thickness and tractography measures in a sample of early and late bilinguals. Thirty-six bilinguals with Spanish as their L1, who learned Basque as their L2 before age 3 (early bilinguals) or after age 6 (late bilinguals), participated. All participants were high-proficient in both languages. In the scanner, they performed two separate tasks during which they were asked to press a button when they saw a colored letter within a given string (perceptual-task) or when they saw an animal word (semantic-task). Whole-brain fMRI analysis reveals no differences between groups. Region-of-interest analysis revealed a similar recruitment of left and right language-related regions in both early and late bilinguals except for the left and right pars triangularis. As compared to late bilinguals, early bilinguals exhibited a different pattern of left triangularis engagement in the interaction between task and language effects. Similarly, early bilinguals showed a more selective recruitment for word versus pseudoword reading in right triangularis. Moreover, functional connectivity analyses confirmed a tighter coactivation among left and right pars triangularis in early, but not in late, bilinguals for reading in L1 relative to reading in L2. Importantly, structural analysis revealed increased cortical thickness in right pars triangularis for early relative to late bilinguals. Additionally, enhanced functional activation for L2-L1 language effects in the left triangularis predicted cortical thinning in their right triangularis counterpart only in early bilinguals. Finally, diffusion MR tractography of the connecting left and right pars triangularis also revealed differences between early and late bilinguals. In sum, our results indicate that the early exposure to two languages led to a more distributed involvement of regions beyond the classical left perisylvian areas in reading. Our findings provide the strongest converging evidence so far of structural and functional changes involving left and right triangularis as a result of L2 AoA in bilingual readers. Acknowledgements Basque Government PhD fellowship from Department of Education, University and Research from the Basque Government ERC-2011-ADG-295362 grant from the European Research Council References Hernandez, Arturo E., Elizabeth A. Woods, and Kailyn AL Bradley (2015). "Neural correlates of single word reading in bilingual children and adults." Brain and language 143: 11-19. Klein, D., Mok, K., Chen, J. K., & Watkins, K. E. (2014). Age of language learning shapes brain structure: a cortical thickness study of bilingual and monolingual individuals. Brain and language, 131, 20-24. Turkeltaub, P. E., Eden, G. F., Jones, K. M., & Zeffiro, T. A. (2002). Meta-analysis of the functional neuroanatomy of single-word reading: method and validation. Neuroimage, 16(3), 765-780 Keywords: Language, bilingualism, DTI, fMRI, reading Conference: International Conference - Educational Neuroscience, Abu Dhabi, United Arab Emirates, 28 Feb - 29 Feb, 2016. Presentation Type: Poster Presentation Topic: Educational Neuroscience Citation: Oliver M, Carreiras M, Iturria Medina Y and Paz-Alonso PM (2016). Age of acquisition of the second language modulates structural and functional dynamics of bilingual reading. Front. Neurosci. Conference Abstract: International Conference - Educational Neuroscience. doi: 10.3389/conf.fnins.2016.92.00025 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Jan 2016; Published Online: 23 Mar 2016. * Correspondence: Miss. Myriam Oliver, Basque Center on Cognition,Brain and Language, San Sebastian-Donostia, Spain, myriam.oliver4@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Myriam Oliver Manuel Carreiras Yasser Iturria Medina Pedro M Paz-Alonso Google Myriam Oliver Manuel Carreiras Yasser Iturria Medina Pedro M Paz-Alonso Google Scholar Myriam Oliver Manuel Carreiras Yasser Iturria Medina Pedro M Paz-Alonso PubMed Myriam Oliver Manuel Carreiras Yasser Iturria Medina Pedro M Paz-Alonso Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

A large part of the development effort of compute-intensive applications is devoted to optimization, i.e., achieving the computation within a finite budget of time, space or energy. Given the complexity of modern architectures, writing simulation applications is often a two-step workflow. Firstly, developers design a sequential program for algorithmic tuning and debugging purposes. Secondly, experts optimize and exploit possible approximations of the original program to scale to the actual problem size. This second step is a tedious, time-consuming and error-prone task. In this paper we investigate language extensions and compiler tools to achieve that task semi-automatically in the context of approximate computing. We identified the semantic and syntactic information necessary for a compiler to automatically handle approximation and adaptive techniques for a particular class of programs. We propose a set of language extensions generic enough to provide the compiler with the useful semantic information when approximation is beneficial. We implemented the compiler infrastructure to exploit these extensions and to automatically generate the adaptively approximated version of a program. We provide an experimental study of the impact and expressiveness of our language extension set on various applications.

Sentence similarity measures have taken an increasingly important role in a variety of applications of text knowledge presentation and discovery. Current methods utilize only semantic or syntactic information. We propose a novel method to calculate sentence similarity, which takes into account both semantic information and word order. The experimental results show that our method outperforms existing methods.