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Sample records for brain language network

  1. Second language experience modulates functional brain network for the native language production in bimodal bilinguals.

    Science.gov (United States)

    Zou, Lijuan; Abutalebi, Jubin; Zinszer, Benjamin; Yan, Xin; Shu, Hua; Peng, Danling; Ding, Guosheng

    2012-09-01

    The functional brain network of a bilingual's first language (L1) plays a crucial role in shaping that of his or her second language (L2). However, it is less clear how L2 acquisition changes the functional network of L1 processing in bilinguals. In this study, we demonstrate that in bimodal (Chinese spoken-sign) bilinguals, the functional network supporting L1 production (spoken language) has been reorganized to accommodate the network underlying L2 production (sign language). Using functional magnetic resonance imaging (fMRI) and a picture naming task, we find greater recruitment of the right supramarginal gyrus (RSMG), the right temporal gyrus (RSTG), and the right superior occipital gyrus (RSOG) for bilingual speakers versus monolingual speakers during L1 production. In addition, our second experiment reveals that these regions reflect either automatic activation of L2 (RSOG) or extra cognitive coordination (RSMG and RSTG) between both languages during L1 production. The functional connectivity between these regions, as well as between other regions that are L1- or L2-specific, is enhanced during L1 production in bimodal bilinguals as compared to their monolingual peers. These findings suggest that L1 production in bimodal bilinguals involves an interaction between L1 and L2, supporting the claim that learning a second language does, in fact, change the functional brain network of the first language. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Language in the aging brain: the network dynamics of cognitive decline and preservation.

    Science.gov (United States)

    Shafto, Meredith A; Tyler, Lorraine K

    2014-10-31

    Language is a crucial and complex lifelong faculty, underpinned by dynamic interactions within and between specialized brain networks. Whereas normal aging impairs specific aspects of language production, most core language processes are robust to brain aging. We review recent behavioral and neuroimaging evidence showing that language systems remain largely stable across the life span and that both younger and older adults depend on dynamic neural responses to linguistic demands. Although some aspects of network dynamics change with age, there is no consistent evidence that core language processes are underpinned by different neural networks in younger and older adults. Copyright © 2014, American Association for the Advancement of Science.

  3. Cross-language differences in the brain network subserving intelligible speech.

    Science.gov (United States)

    Ge, Jianqiao; Peng, Gang; Lyu, Bingjiang; Wang, Yi; Zhuo, Yan; Niu, Zhendong; Tan, Li Hai; Leff, Alexander P; Gao, Jia-Hong

    2015-03-10

    How is language processed in the brain by native speakers of different languages? Is there one brain system for all languages or are different languages subserved by different brain systems? The first view emphasizes commonality, whereas the second emphasizes specificity. We investigated the cortical dynamics involved in processing two very diverse languages: a tonal language (Chinese) and a nontonal language (English). We used functional MRI and dynamic causal modeling analysis to compute and compare brain network models exhaustively with all possible connections among nodes of language regions in temporal and frontal cortex and found that the information flow from the posterior to anterior portions of the temporal cortex was commonly shared by Chinese and English speakers during speech comprehension, whereas the inferior frontal gyrus received neural signals from the left posterior portion of the temporal cortex in English speakers and from the bilateral anterior portion of the temporal cortex in Chinese speakers. Our results revealed that, although speech processing is largely carried out in the common left hemisphere classical language areas (Broca's and Wernicke's areas) and anterior temporal cortex, speech comprehension across different language groups depends on how these brain regions interact with each other. Moreover, the right anterior temporal cortex, which is crucial for tone processing, is equally important as its left homolog, the left anterior temporal cortex, in modulating the cortical dynamics in tone language comprehension. The current study pinpoints the importance of the bilateral anterior temporal cortex in language comprehension that is downplayed or even ignored by popular contemporary models of speech comprehension.

  4. Neurological impressions on the organization of language networks in the human brain.

    Science.gov (United States)

    Oliveira, Fabricio Ferreira de; Marin, Sheilla de Medeiros Correia; Bertolucci, Paulo Henrique Ferreira

    2017-01-01

    More than 95% of right-handed individuals, as well as almost 80% of left-handed individuals, have left hemisphere dominance for language. The perisylvian networks of the dominant hemisphere tend to be the most important language systems in human brains, usually connected by bidirectional fibres originated from the superior longitudinal fascicle/arcuate fascicle system and potentially modifiable by learning. Neuroplasticity mechanisms take place to preserve neural functions after brain injuries. Language is dependent on a hierarchical interlinkage of serial and parallel processing areas in distinct brain regions considered to be elementary processing units. Whereas aphasic syndromes typically result from injuries to the dominant hemisphere, the extent of the distribution of language functions seems to be variable for each individual. Review of the literature Results: Several theories try to explain the organization of language networks in the human brain from a point of view that involves either modular or distributed processing or sometimes both. The most important evidence for each approach is discussed under the light of modern theories of organization of neural networks. Understanding the connectivity patterns of language networks may provide deeper insights into language functions, supporting evidence-based rehabilitation strategies that focus on the enhancement of language organization for patients with aphasic syndromes.

  5. Aberrant topologies and reconfiguration pattern of functional brain network in children with second language reading impairment.

    Science.gov (United States)

    Liu, Lanfang; Li, Hehui; Zhang, Manli; Wang, Zhengke; Wei, Na; Liu, Li; Meng, Xiangzhi; Ding, Guosheng

    2016-07-01

    Prior work has extensively studied neural deficits in children with reading impairment (RI) in their native language but has rarely examined those of RI children in their second language (L2). A recent study revealed that the function of the local brain regions was disrupted in children with RI in L2, but it is not clear whether the disruption also occurs at a large-scale brain network level. Using fMRI and graph theoretical analysis, we explored the topology of the whole-brain functional network during a phonological rhyming task and network reconfigurations across task and short resting phases in Chinese children with English reading impairment versus age-matched typically developing (TD) children. We found that, when completing the phonological task, the RI group exhibited higher local network efficiency and network modularity compared with the TD group. When switching between the phonological task and the short resting phase, the RI group showed difficulty with network reconfiguration, as reflected in fewer changes in the local efficiency and modularity properties and less rearrangement of the modular communities. These findings were reproducible after controlling for the effects of in-scanner accuracy, participant gender, and L1 reading performance. The results from the whole-brain network analyses were largely replicated in the task-activated network. These findings provide preliminary evidence supporting that RI in L2 is associated with not only abnormal functional network organization but also poor flexibility of the neural system in responding to changing cognitive demands. © 2016 John Wiley & Sons Ltd.

  6. Intention processing in communication: a common brain network for language and gestures.

    Science.gov (United States)

    Enrici, Ivan; Adenzato, Mauro; Cappa, Stefano; Bara, Bruno G; Tettamanti, Marco

    2011-09-01

    Human communicative competence is based on the ability to process a specific class of mental states, namely, communicative intention. The present fMRI study aims to analyze whether intention processing in communication is affected by the expressive means through which a communicative intention is conveyed, that is, the linguistic or extralinguistic gestural means. Combined factorial and conjunction analyses were used to test two sets of predictions: first, that a common brain network is recruited for the comprehension of communicative intentions independently of the modality through which they are conveyed; second, that additional brain areas are specifically recruited depending on the communicative modality used, reflecting distinct sensorimotor gateways. Our results clearly showed that a common neural network is engaged in communicative intention processing independently of the modality used. This network includes the precuneus, the left and right posterior STS and TPJ, and the medial pFC. Additional brain areas outside those involved in intention processing are specifically engaged by the particular communicative modality, that is, a peri-sylvian language network for the linguistic modality and a sensorimotor network for the extralinguistic modality. Thus, common representation of communicative intention may be accessed by modality-specific gateways, which are distinct for linguistic versus extralinguistic expressive means. Taken together, our results indicate that the information acquired by different communicative modalities is equivalent from a mental processing standpoint, in particular, at the point at which the actor's communicative intention has to be reconstructed.

  7. Large-scale brain networks underlying language acquisition in early infancy

    Directory of Open Access Journals (Sweden)

    Fumitaka eHomae

    2011-05-01

    Full Text Available A critical issue in human development is that of whether the language-related areas in the left frontal and temporal regions work as a functional network in preverbal infants. Here, we used 94-channel near-infrared spectroscopy (NIRS to reveal the functional networks in the brains of sleeping 3-month-old infants with and without presenting speech sounds. During the first 3 min, we measured spontaneous brain activation (period 1. After period 1, we provided stimuli by playing Japanese sentences for 3 min (period 2. Finally, we measured brain activation for 3 min without providing the stimulus (period 3, as in period 1. We found that not only the bilateral temporal and temporoparietal regions but also the prefrontal and occipital regions showed oxygenated hemoglobin (oxy-Hb signal increases and deoxygenated hemoglobin (deoxy-Hb signal decreases when speech sounds were presented to infants. By calculating time-lagged cross-correlations and coherences of oxy-Hb signals between channels, we tested the functional connectivity for the 3 periods. The oxy-Hb signals in neighboring channels, as well as their homologous channels in the contralateral hemisphere, showed high correlation coefficients in period 1. Similar correlations were observed in period 2; however, the number of channels showing high correlations was higher in the ipsilateral hemisphere, especially in the anterior-posterior direction. The functional connectivity in period 3 showed a close relationship between the frontal and temporal regions, which was less prominent in period 1, indicating that these regions form the functional networks and work as a hysteresis system that has memory of the previous inputs. We propose a hypothesis that the spatiotemporally large-scale brain networks, including the frontal and temporal regions, underlie speech processing in infants and they might play important roles in language acquisition during infancy.

  8. Stimulating the Brain's Language Network: Syntactic Ambiguity Resolution after TMS to the Inferior Frontal Gyrus and Middle Temporal Gyrus

    NARCIS (Netherlands)

    Acheson, D.J.; Hagoort, P.

    2013-01-01

    The posterior middle temporal gyrus (MTG) and inferior frontal gyrus (IFG) are two critical nodes of the brain's language network. Previous neuroimaging evidence has supported a dissociation in language comprehension in which parts of the MTG are involved in the retrieval of lexical syntactic

  9. Whole-brain functional connectivity during acquisition of novel grammar: Distinct functional networks depend on language learning abilities.

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    Kepinska, Olga; de Rover, Mischa; Caspers, Johanneke; Schiller, Niels O

    2017-03-01

    In an effort to advance the understanding of brain function and organisation accompanying second language learning, we investigate the neural substrates of novel grammar learning in a group of healthy adults, consisting of participants with high and average language analytical abilities (LAA). By means of an Independent Components Analysis, a data-driven approach to functional connectivity of the brain, the fMRI data collected during a grammar-learning task were decomposed into maps representing separate cognitive processes. These included the default mode, task-positive, working memory, visual, cerebellar and emotional networks. We further tested for differences within the components, representing individual differences between the High and Average LAA learners. We found high analytical abilities to be coupled with stronger contributions to the task-positive network from areas adjacent to bilateral Broca's region, stronger connectivity within the working memory network and within the emotional network. Average LAA participants displayed stronger engagement within the task-positive network from areas adjacent to the right-hemisphere homologue of Broca's region and typical to lower level processing (visual word recognition), and increased connectivity within the default mode network. The significance of each of the identified networks for the grammar learning process is presented next to a discussion on the established markers of inter-individual learners' differences. We conclude that in terms of functional connectivity, the engagement of brain's networks during grammar acquisition is coupled with one's language learning abilities. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Functional mapping of language networks in the normal brain using a word-association task

    International Nuclear Information System (INIS)

    Ghosh, Shantanu; Basu, Amrita; Kumaran, Senthil S; Khushu, Subash

    2010-01-01

    Language functions are known to be affected in diverse neurological conditions, including ischemic stroke, traumatic brain injury, and brain tumors. Because language networks are extensive, interpretation of functional data depends on the task completed during evaluation. The aim was to map the hemodynamic consequences of word association using functional magnetic resonance imaging (fMRI) in normal human subjects. Ten healthy subjects underwent fMRI scanning with a postlexical access semantic association task vs lexical processing task. The fMRI protocol involved a T2*-weighted gradient-echo echo-planar imaging (GE-EPI) sequence (TR 4523 ms, TE 64 ms, flip angle 90°) with alternate baseline and activation blocks. A total of 78 scans were taken (interscan interval = 3 s) with a total imaging time of 587 s. Functional data were processed in Statistical Parametric Mapping software (SPM2) with 8-mm Gaussian kernel by convolving the blood oxygenation level-dependent (BOLD) signal with an hemodynamic response function estimated by general linear method to generate SPM{t} and SPM{F} maps. Single subject analysis of the functional data (FWE-corrected, P≤0.001) revealed extensive activation in the frontal lobes, with overlaps among middle frontal gyrus (MFG), superior, and inferior frontal gyri. BOLD activity was also found in the medial frontal gyrus, middle occipital gyrus (MOG), anterior fusiform gyrus, superior and inferior parietal lobules, and to a smaller extent, the thalamus and right anterior cerebellum. Group analysis (FWE-corrected, P≤0.001) revealed neural recruitment of bilateral lingual gyri, left MFG, bilateral MOG, left superior occipital gyrus, left fusiform gyrus, bilateral thalami, and right cerebellar areas. Group data analysis revealed a cerebellar–occipital–fusiform–thalamic network centered around bilateral lingual gyri for word association, thereby indicating how these areas facilitate language comprehension by activating a semantic

  11. Aberrant Topologies and Reconfiguration Pattern of Functional Brain Network in Children with Second Language Reading Impairment

    Science.gov (United States)

    Liu, Lanfang; Li, Hehui; Zhang, Manli; Wang, Zhengke; Wei, Na; Liu, Li; Meng, Xiangzhi; Ding, Guosheng

    2016-01-01

    Prior work has extensively studied neural deficits in children with reading impairment (RI) in their native language but has rarely examined those of RI children in their second language (L2). A recent study revealed that the function of the local brain regions was disrupted in children with RI in L2, but it is not clear whether the disruption…

  12. Brain Tumors - Multiple Languages

    Science.gov (United States)

    ... Supplements Videos & Tools You Are Here: Home → Multiple Languages → All Health Topics → Brain Tumors URL of this page: https://medlineplus.gov/ ... V W XYZ List of All Topics All Brain Tumors - Multiple Languages To use the sharing features on this page, ...

  13. Brain Diseases - Multiple Languages

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    ... Supplements Videos & Tools You Are Here: Home → Multiple Languages → All Health Topics → Brain Diseases URL of this page: https://medlineplus.gov/ ... V W XYZ List of All Topics All Brain Diseases - Multiple Languages To use the sharing features on this page, ...

  14. Language differences in the brain network for reading in naturalistic story reading and lexical decision.

    Directory of Open Access Journals (Sweden)

    Xiaojuan Wang

    Full Text Available Differences in how writing systems represent language raise important questions about whether there could be a universal functional architecture for reading across languages. In order to study potential language differences in the neural networks that support reading skill, we collected fMRI data from readers of alphabetic (English and morpho-syllabic (Chinese writing systems during two reading tasks. In one, participants read short stories under conditions that approximate natural reading, and in the other, participants decided whether individual stimuli were real words or not. Prior work comparing these two writing systems has overwhelmingly used meta-linguistic tasks, generally supporting the conclusion that the reading system is organized differently for skilled readers of Chinese and English. We observed that language differences in the reading network were greatly dependent on task. In lexical decision, a pattern consistent with prior research was observed in which the Middle Frontal Gyrus (MFG and right Fusiform Gyrus (rFFG were more active for Chinese than for English, whereas the posterior temporal sulcus was more active for English than for Chinese. We found a very different pattern of language effects in a naturalistic reading paradigm, during which significant differences were only observed in visual regions not typically considered specific to the reading network, and the middle temporal gyrus, which is thought to be important for direct mapping of orthography to semantics. Indeed, in areas that are often discussed as supporting distinct cognitive or linguistic functions between the two languages, we observed interaction. Specifically, language differences were most pronounced in MFG and rFFG during the lexical decision task, whereas no language differences were observed in these areas during silent reading of text for comprehension.

  15. Language differences in the brain network for reading in naturalistic story reading and lexical decision.

    Science.gov (United States)

    Wang, Xiaojuan; Yang, Jianfeng; Yang, Jie; Mencl, W Einar; Shu, Hua; Zevin, Jason David

    2015-01-01

    Differences in how writing systems represent language raise important questions about whether there could be a universal functional architecture for reading across languages. In order to study potential language differences in the neural networks that support reading skill, we collected fMRI data from readers of alphabetic (English) and morpho-syllabic (Chinese) writing systems during two reading tasks. In one, participants read short stories under conditions that approximate natural reading, and in the other, participants decided whether individual stimuli were real words or not. Prior work comparing these two writing systems has overwhelmingly used meta-linguistic tasks, generally supporting the conclusion that the reading system is organized differently for skilled readers of Chinese and English. We observed that language differences in the reading network were greatly dependent on task. In lexical decision, a pattern consistent with prior research was observed in which the Middle Frontal Gyrus (MFG) and right Fusiform Gyrus (rFFG) were more active for Chinese than for English, whereas the posterior temporal sulcus was more active for English than for Chinese. We found a very different pattern of language effects in a naturalistic reading paradigm, during which significant differences were only observed in visual regions not typically considered specific to the reading network, and the middle temporal gyrus, which is thought to be important for direct mapping of orthography to semantics. Indeed, in areas that are often discussed as supporting distinct cognitive or linguistic functions between the two languages, we observed interaction. Specifically, language differences were most pronounced in MFG and rFFG during the lexical decision task, whereas no language differences were observed in these areas during silent reading of text for comprehension.

  16. Interaction of language, auditory and memory brain networks in auditory verbal hallucinations

    NARCIS (Netherlands)

    Curcic-Blake, Branislava; Ford, Judith M.; Hubl, Daniela; Orlov, Natasza D.; Sommer, Iris E.; Waters, Flavie; Allen, Paul; Jardri, Renaud; Woodruff, Peter W.; David, Olivier; Mulert, Christoph; Woodward, Todd S.; Aleman, Andre

    Auditory verbal hallucinations (AVH) occur in psychotic disorders, but also as a symptom of other conditions and even in healthy people. Several current theories on the origin of AVH converge, with neuroimaging studies suggesting that the language, auditory and memory/limbic networks are of

  17. Language conflict in the bilingual brain.

    Science.gov (United States)

    van Heuven, Walter J B; Schriefers, Herbert; Dijkstra, Ton; Hagoort, Peter

    2008-11-01

    The large majority of humankind is more or less fluent in 2 or even more languages. This raises the fundamental question how the language network in the brain is organized such that the correct target language is selected at a particular occasion. Here we present behavioral and functional magnetic resonance imaging data showing that bilingual processing leads to language conflict in the bilingual brain even when the bilinguals' task only required target language knowledge. This finding demonstrates that the bilingual brain cannot avoid language conflict, because words from the target and nontarget languages become automatically activated during reading. Importantly, stimulus-based language conflict was found in brain regions in the LIPC associated with phonological and semantic processing, whereas response-based language conflict was only found in the pre-supplementary motor area/anterior cingulate cortex when language conflict leads to response conflicts.

  18. Overlap and Differences in Brain Networks Underlying the Processing of Complex Sentence Structures in Second Language Users Compared with Native Speakers.

    Science.gov (United States)

    Weber, Kirsten; Luther, Lisa; Indefrey, Peter; Hagoort, Peter

    2016-05-01

    When we learn a second language later in life, do we integrate it with the established neural networks in place for the first language or is at least a partially new network recruited? While there is evidence that simple grammatical structures in a second language share a system with the native language, the story becomes more multifaceted for complex sentence structures. In this study, we investigated the underlying brain networks in native speakers compared with proficient second language users while processing complex sentences. As hypothesized, complex structures were processed by the same large-scale inferior frontal and middle temporal language networks of the brain in the second language, as seen in native speakers. These effects were seen both in activations and task-related connectivity patterns. Furthermore, the second language users showed increased task-related connectivity from inferior frontal to inferior parietal regions of the brain, regions related to attention and cognitive control, suggesting less automatic processing for these structures in a second language.

  19. Interaction of language, auditory and memory brain networks in auditory verbal hallucinations.

    Science.gov (United States)

    Ćurčić-Blake, Branislava; Ford, Judith M; Hubl, Daniela; Orlov, Natasza D; Sommer, Iris E; Waters, Flavie; Allen, Paul; Jardri, Renaud; Woodruff, Peter W; David, Olivier; Mulert, Christoph; Woodward, Todd S; Aleman, André

    2017-01-01

    Auditory verbal hallucinations (AVH) occur in psychotic disorders, but also as a symptom of other conditions and even in healthy people. Several current theories on the origin of AVH converge, with neuroimaging studies suggesting that the language, auditory and memory/limbic networks are of particular relevance. However, reconciliation of these theories with experimental evidence is missing. We review 50 studies investigating functional (EEG and fMRI) and anatomic (diffusion tensor imaging) connectivity in these networks, and explore the evidence supporting abnormal connectivity in these networks associated with AVH. We distinguish between functional connectivity during an actual hallucination experience (symptom capture) and functional connectivity during either the resting state or a task comparing individuals who hallucinate with those who do not (symptom association studies). Symptom capture studies clearly reveal a pattern of increased coupling among the auditory, language and striatal regions. Anatomical and symptom association functional studies suggest that the interhemispheric connectivity between posterior auditory regions may depend on the phase of illness, with increases in non-psychotic individuals and first episode patients and decreases in chronic patients. Leading hypotheses involving concepts as unstable memories, source monitoring, top-down attention, and hybrid models of hallucinations are supported in part by the published connectivity data, although several caveats and inconsistencies remain. Specifically, possible changes in fronto-temporal connectivity are still under debate. Precise hypotheses concerning the directionality of connections deduced from current theoretical approaches should be tested using experimental approaches that allow for discrimination of competing hypotheses. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  20. Presurgical brain mapping of the language network in patients with brain tumors using resting-state fMRI: Comparison with task fMRI.

    Science.gov (United States)

    Sair, Haris I; Yahyavi-Firouz-Abadi, Noushin; Calhoun, Vince D; Airan, Raag D; Agarwal, Shruti; Intrapiromkul, Jarunee; Choe, Ann S; Gujar, Sachin K; Caffo, Brian; Lindquist, Martin A; Pillai, Jay J

    2016-03-01

    To compare language networks derived from resting-state fMRI (rs-fMRI) with task-fMRI in patients with brain tumors and investigate variables that affect rs-fMRI vs task-fMRI concordance. Independent component analysis (ICA) of rs-fMRI was performed with 20, 30, 40, and 50 target components (ICA20 to ICA50) and language networks identified for patients presenting for presurgical fMRI mapping between 1/1/2009 and 7/1/2015. 49 patients were analyzed fulfilling criteria for presence of brain tumors, no prior brain surgery, and adequate task-fMRI performance. Rs-vs-task-fMRI concordance was measured using Dice coefficients across varying fMRI thresholds before and after noise removal. Multi-thresholded Dice coefficient volume under the surface (DiceVUS) and maximum Dice coefficient (MaxDice) were calculated. One-way Analysis of Variance (ANOVA) was performed to determine significance of DiceVUS and MaxDice between the four ICA order groups. Age, Sex, Handedness, Tumor Side, Tumor Size, WHO Grade, number of scrubbed volumes, image intensity root mean square (iRMS), and mean framewise displacement (FD) were used as predictors for VUS in a linear regression. Artificial elevation of rs-fMRI vs task-fMRI concordance is seen at low thresholds due to noise. Noise-removed group-mean DiceVUS and MaxDice improved as ICA order increased, however ANOVA demonstrated no statistically significant difference between the four groups. Linear regression demonstrated an association between iRMS and DiceVUS for ICA30-50, and iRMS and MaxDice for ICA50. Overall there is moderate group level rs-vs-task fMRI language network concordance, however substantial subject-level variability exists; iRMS may be used to determine reliability of rs-fMRI derived language networks. © 2015 Wiley Periodicals, Inc.

  1. Traumatic Brain Injury - Multiple Languages

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    ... Supplements Videos & Tools You Are Here: Home → Multiple Languages → All Health Topics → Traumatic Brain Injury URL of this page: https://medlineplus.gov/ ... W XYZ List of All Topics All Traumatic Brain Injury - Multiple Languages To use the sharing features on this page, ...

  2. Evolution of Brain and Language

    Science.gov (United States)

    Schoenemann, P. Thomas

    2009-01-01

    The evolution of language and the evolution of the brain are tightly interlinked. Language evolution represents a special kind of adaptation, in part because language is a complex behavior (as opposed to a physical feature) but also because changes are adaptive only to the extent that they increase either one's understanding of others, or one's…

  3. How does language distance between L1 and L2 affect the L2 brain network? An fMRI study of Korean-Chinese-English trilinguals.

    Science.gov (United States)

    Kim, Say Young; Qi, Ting; Feng, Xiaoxia; Ding, Guosheng; Liu, Li; Cao, Fan

    2016-04-01

    The present study tested the hypothesis that language distance between first language (L1) and second language (L2) influences the assimilation and accommodation pattern in Korean-Chinese-English trilinguals. The distance between English and Korean is smaller than that between Chinese and Korean in terms of orthographic transparency, because both English and Korean are alphabetic, whereas Chinese is logographic. During fMRI, Korean trilingual participants performed a visual rhyming judgment task in three languages (Korean: KK, Chinese: KC, English: KE). Two L1 control groups were native Chinese and English speakers performing the task in their native languages (CC and EE, respectively). The general pattern of brain activation of KC was more similar to that of CC than KK, suggesting accommodation. Higher accuracy in KC was associated with decreased activation in regions of the KK network, suggesting reduced assimilation. In contrast, the brain activation of KE was more similar to that of KK than EE, suggesting assimilation. Higher accuracy in KE was associated with decreased activation in regions of the EE network, suggesting reduced accommodation. Finally, an ROI analysis on the left middle frontal gyrus revealed greater activation for KC than for KE, suggesting its selective involvement in the L2 with more arbitrary mapping between orthography and phonology (i.e., Chinese). Taken together, the brain network involved in L2 reading is similar to the L1 network when L2 and L1 are similar in orthographic transparency, while significant accommodation is expected when L2 is more opaque than L1. Copyright © 2015. Published by Elsevier Inc.

  4. Setting the Frame: The Human Brain Activates a Basic Low-Frequency Network for Language Processing

    NARCIS (Netherlands)

    Lohmann, G.; Hoehl, S.; Brauer, J.; Danielmeier, C.; Bornkessel, I.D.; Bahlmann, J.; Turner, R.; Friederici, A.D.

    2010-01-01

    Low-frequency fluctuations (LFFs) are a major source of variation in fMRI data. This has been established in numerous experiments-particularly in the resting state. Here we investigate LFFs in a task-dependent setting. We hypothesized that LFFs may contain information about cognitive networks that

  5. Brain and language: evidence for neural multifunctionality.

    Science.gov (United States)

    Cahana-Amitay, Dalia; Albert, Martin L

    2014-01-01

    This review paper presents converging evidence from studies of brain damage and longitudinal studies of language in aging which supports the following thesis: the neural basis of language can best be understood by the concept of neural multifunctionality. In this paper the term "neural multifunctionality" refers to incorporation of nonlinguistic functions into language models of the intact brain, reflecting a multifunctional perspective whereby a constant and dynamic interaction exists among neural networks subserving cognitive, affective, and praxic functions with neural networks specialized for lexical retrieval, sentence comprehension, and discourse processing, giving rise to language as we know it. By way of example, we consider effects of executive system functions on aspects of semantic processing among persons with and without aphasia, as well as the interaction of executive and language functions among older adults. We conclude by indicating how this multifunctional view of brain-language relations extends to the realm of language recovery from aphasia, where evidence of the influence of nonlinguistic factors on the reshaping of neural circuitry for aphasia rehabilitation is clearly emerging.

  6. Network-based analysis reveals stronger local diffusion-based connectivity and different correlations with oral language skills in brains of children with high functioning autism spectrum disorders.

    Science.gov (United States)

    Li, Hai; Xue, Zhong; Ellmore, Timothy M; Frye, Richard E; Wong, Stephen T C

    2014-02-01

    Neuroimaging has uncovered both long-range and short-range connectivity abnormalities in the brains of individuals with autism spectrum disorders (ASD). However, the precise connectivity abnormalities and the relationship between these abnormalities and cognition and ASD symptoms have been inconsistent across studies. Indeed, studies find both increases and decreases in connectivity, suggesting that connectivity changes in the ASD brain are not merely due to abnormalities in specific connections, but rather, due to changes in the structure of the network in which the brain areas interact (i.e., network topology). In this study, we examined the differences in the network topology between high-functioning ASD patients and age and gender matched typically developing (TD) controls. After quantitatively characterizing the whole-brain connectivity network using diffusion tensor imaging (DTI) data, we searched for brain regions with different connectivity between ASD and TD. A measure of oral language ability was then correlated with the connectivity changes to determine the functional significance of such changes. Whole-brain connectivity measures demonstrated greater local connectivity and shorter path length in ASD as compared to TD. Stronger local connectivity was found in ASD, especially in regions such as the left superior parietal lobule, the precuneus and angular gyrus, and the right supramarginal gyrus. The relationship between oral language ability and local connectivity within these regions was significantly different between ASD and TD. Stronger local connectivity was associated with better performance in ASD and poorer performance in TD. This study supports the notion that increased local connectivity is compensatory for supporting cognitive function in ASD. Copyright © 2012 Wiley Periodicals, Inc.

  7. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

    Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

  8. Foreign Language Study and the Brain.

    Science.gov (United States)

    LeLoup, Jean W.; Ponterio, Robert

    2003-01-01

    Provides information on foreign language study and the brain and highlights a Web site called Foreign Language Study and the Brain. The Web site is in Spanish and English and provides information on brain-sensitive activities that foster memory storage and language retrieval. Recent research on the brain and general recommendations for classroom…

  9. Multilayer Brain Networks

    Science.gov (United States)

    Vaiana, Michael; Muldoon, Sarah Feldt

    2018-01-01

    The field of neuroscience is facing an unprecedented expanse in the volume and diversity of available data. Traditionally, network models have provided key insights into the structure and function of the brain. With the advent of big data in neuroscience, both more sophisticated models capable of characterizing the increasing complexity of the data and novel methods of quantitative analysis are needed. Recently, multilayer networks, a mathematical extension of traditional networks, have gained increasing popularity in neuroscience due to their ability to capture the full information of multi-model, multi-scale, spatiotemporal data sets. Here, we review multilayer networks and their applications in neuroscience, showing how incorporating the multilayer framework into network neuroscience analysis has uncovered previously hidden features of brain networks. We specifically highlight the use of multilayer networks to model disease, structure-function relationships, network evolution, and link multi-scale data. Finally, we close with a discussion of promising new directions of multilayer network neuroscience research and propose a modified definition of multilayer networks designed to unite and clarify the use of the multilayer formalism in describing real-world systems.

  10. Mapping Language Problems in the Brain

    Science.gov (United States)

    ... Print this issue Mapping Language Problems in the Brain En español Send us your comments We often ... more about how language is organized in the brain, an NIH-funded research team studied people with ...

  11. Overlap and differences in brain networks underlying the processing of complex sentence structures in second language users compared with native speakers

    NARCIS (Netherlands)

    Weber, K.M.; Luther, L.M.; Indefrey, P.; Hagoort, P.

    2016-01-01

    When we learn a second language later in life, do we integrate it with the established neural networks in place for the first language or is at least a partially new network recruited? While there is evidence that simple grammatical structures in a second language share a system with the native

  12. Two languages in mind: Bilingualism as a tool to investigate language, cognition, and the brain.

    Science.gov (United States)

    Kroll, Judith F; Bobb, Susan C; Hoshino, Noriko

    2014-06-01

    A series of discoveries in the last two decades has changed the way we think about bilingualism and its implications for language and cognition. One is that both languages are always active. The parallel activation of the two languages is thought to give rise to competition that imposes demands on the bilingual to control the language not in use to achieve fluency in the target language. The second is that there are consequences of bilingualism that affect the native as well as the second language. The native language changes in response to second language use. The third is that the consequences of bilingualism are not limited to language but appear to reflect a reorganization of brain networks that hold implications for the ways in which bilinguals negotiate cognitive competition more generally. The focus of recent research on bilingualism has been to understand the relation between these discoveries and the implications they hold for language, cognition, and the brain across the lifespan.

  13. Networks for memory, perception, and decision-making, and beyond to how the syntax for language might be implemented in the brain.

    Science.gov (United States)

    Rolls, Edmund T; Deco, Gustavo

    2015-09-24

    Neural principles that provide a foundation for memory, perception, and decision-making include place coding with sparse distributed representations, associative synaptic modification, and attractor networks in which the storage capacity is in the order of the number of associatively modifiable recurrent synapses on any one neuron. Based on those and further principles of cortical computation, hypotheses are explored in which syntax is encoded in the cortex using sparse distributed place coding. Each cortical module 2-3 mm in diameter is proposed to be formed of a local attractor neuronal network with a capacity in the order of 10,000 words (e.g. subjects, verbs or objects depending on the module). Such a system may form a deep language-of-thought layer. For the information to be communicated to other people, the modules in which the neurons are firing which encode the syntactic role, as well as which neurons are firing to specify the words, must be communicated. It is proposed that one solution to this (used in English) is temporal order encoding, for example subject-verb-object. It is shown with integrate-and-fire simulations that this order encoding could be implemented by weakly forward-coupled subject-verb-object modules. A related system can decode a temporal sequence. This approach based on known principles of cortical computation needs to be extended to investigate further whether it could form a biological foundation for the implementation of language in the brain. This article is part of a Special Issue entitled SI: Brain and Memory. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Sign Language and the Brain: A Review

    Science.gov (United States)

    Campbell, Ruth; MacSweeney, Mairead; Waters, Dafydd

    2008-01-01

    How are signed languages processed by the brain? This review briefly outlines some basic principles of brain structure and function and the methodological principles and techniques that have been used to investigate this question. We then summarize a number of different studies exploring brain activity associated with sign language processing…

  15. Reorganization of the Cerebro-Cerebellar Network of Language Production in Patients with Congenital Left-Hemispheric Brain Lesions

    Science.gov (United States)

    Lidzba, K.; Wilke, M.; Staudt, M.; Krageloh-Mann, I.; Grodd, W.

    2008-01-01

    Patients with congenital lesions of the left cerebral hemisphere may reorganize language functions into the right hemisphere. In these patients, language production is represented homotopically to the left-hemispheric language areas. We studied cerebellar activation in five patients with congenital lesions of the left cerebral hemisphere to assess…

  16. Self-government of complex reading and writing brains informed by cingulo-opercular network for adaptive control and working memory components for language learning.

    Science.gov (United States)

    Richards, Todd L; Abbott, Robert D; Yagle, Kevin; Peterson, Dan; Raskind, Wendy; Berninger, Virginia W

    2017-01-01

    To understand mental self-government of the developing reading and writing brain, correlations of clustering coefficients on fMRI reading or writing tasks with BASC 2 Adaptivity ratings (time 1 only) or working memory components (time 1 before and time 2 after instruction previously shown to improve achievement and change magnitude of fMRI connectivity) were investigated in 39 students in grades 4 to 9 who varied along a continuum of reading and writing skills. A Philips 3T scanner measured connectivity during six leveled fMRI reading tasks (subword-letters and sounds, word-word-specific spellings or affixed words, syntax comprehension-with and without homonym foils or with and without affix foils, and text comprehension) and three fMRI writing tasks-writing next letter in alphabet, adding missing letter in word spelling, and planning for composing. The Brain Connectivity Toolbox generated clustering coefficients based on the cingulo-opercular (CO) network; after controlling for multiple comparisons and movement, significant fMRI connectivity clustering coefficients for CO were identified in 8 brain regions bilaterally (cingulate gyrus, superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, superior temporal gyrus, insula, cingulum-cingulate gyrus, and cingulum-hippocampus). BASC2 Parent Ratings for Adaptivity were correlated with CO clustering coefficients on three reading tasks (letter-sound, word affix judgments and sentence comprehension) and one writing task (writing next letter in alphabet). Before instruction, each behavioral working memory measure (phonology, orthography, morphology, and syntax coding, phonological and orthographic loops for integrating internal language and output codes, and supervisory focused and switching attention) correlated significantly with at least one CO clustering coefficient. After instruction, the patterning of correlations changed with new correlations emerging. Results show that the reading and writing brain

  17. The brain's default mode network.

    Science.gov (United States)

    Raichle, Marcus E

    2015-07-08

    The brain's default mode network consists of discrete, bilateral and symmetrical cortical areas, in the medial and lateral parietal, medial prefrontal, and medial and lateral temporal cortices of the human, nonhuman primate, cat, and rodent brains. Its discovery was an unexpected consequence of brain-imaging studies first performed with positron emission tomography in which various novel, attention-demanding, and non-self-referential tasks were compared with quiet repose either with eyes closed or with simple visual fixation. The default mode network consistently decreases its activity when compared with activity during these relaxed nontask states. The discovery of the default mode network reignited a longstanding interest in the significance of the brain's ongoing or intrinsic activity. Presently, studies of the brain's intrinsic activity, popularly referred to as resting-state studies, have come to play a major role in studies of the human brain in health and disease. The brain's default mode network plays a central role in this work.

  18. Controllability of structural brain networks

    Science.gov (United States)

    Gu, Shi; Pasqualetti, Fabio; Cieslak, Matthew; Telesford, Qawi K.; Yu, Alfred B.; Kahn, Ari E.; Medaglia, John D.; Vettel, Jean M.; Miller, Michael B.; Grafton, Scott T.; Bassett, Danielle S.

    2015-10-01

    Cognitive function is driven by dynamic interactions between large-scale neural circuits or networks, enabling behaviour. However, fundamental principles constraining these dynamic network processes have remained elusive. Here we use tools from control and network theories to offer a mechanistic explanation for how the brain moves between cognitive states drawn from the network organization of white matter microstructure. Our results suggest that densely connected areas, particularly in the default mode system, facilitate the movement of the brain to many easily reachable states. Weakly connected areas, particularly in cognitive control systems, facilitate the movement of the brain to difficult-to-reach states. Areas located on the boundary between network communities, particularly in attentional control systems, facilitate the integration or segregation of diverse cognitive systems. Our results suggest that structural network differences between cognitive circuits dictate their distinct roles in controlling trajectories of brain network function.

  19. Language Networks as Complex Systems

    Science.gov (United States)

    Lee, Max Kueiming; Ou, Sheue-Jen

    2008-01-01

    Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…

  20. Neurolinguistic processing when the brain matures without language.

    Science.gov (United States)

    Mayberry, Rachel I; Davenport, Tristan; Roth, Austin; Halgren, Eric

    2018-02-01

    The extent to which development of the brain language system is modulated by the temporal onset of linguistic experience relative to post-natal brain maturation is unknown. This crucial question cannot be investigated with the hearing population because spoken language is ubiquitous in the environment of newborns. Deafness blocks infants' language experience in a spoken form, and in a signed form when it is absent from the environment. Using anatomically constrained magnetoencephalography, aMEG, we neuroimaged lexico-semantic processing in a deaf adult whose linguistic experience began in young adulthood. Despite using language for 30 years after initially learning it, this individual exhibited limited neural response in the perisylvian language areas to signed words during the 300-400 ms temporal window, suggesting that the brain language system requires linguistic experience during brain growth to achieve functionality. The present case study primarily exhibited neural activations in response to signed words in dorsolateral superior parietal and occipital areas bilaterally, replicating the neural patterns exhibited by two previously case studies who matured without language until early adolescence (Ferjan Ramirez N, Leonard MK, Torres C, Hatrak M, Halgren E, Mayberry RI. 2014). The dorsal pathway appears to assume the task of processing words when the brain matures without experiencing the form-meaning network of a language. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Brain correlates of constituent structure in sign language comprehension.

    Science.gov (United States)

    Moreno, Antonio; Limousin, Fanny; Dehaene, Stanislas; Pallier, Christophe

    2017-11-21

    During sentence processing, areas of the left superior temporal sulcus, inferior frontal gyrus and left basal ganglia exhibit a systematic increase in brain activity as a function of constituent size, suggesting their involvement in the computation of syntactic and semantic structures. Here, we asked whether these areas play a universal role in language and therefore contribute to the processing of non-spoken sign language. Congenitally deaf adults who acquired French sign language as a first language and written French as a second language were scanned while watching sequences of signs in which the size of syntactic constituents was manipulated. An effect of constituent size was found in the basal ganglia, including the head of the caudate and the putamen. A smaller effect was also detected in temporal and frontal regions previously shown to be sensitive to constituent size in written language in hearing French subjects (Pallier et al., 2011). When the deaf participants read sentences versus word lists, the same network of language areas was observed. While reading and sign language processing yielded identical effects of linguistic structure in the basal ganglia, the effect of structure was stronger in all cortical language areas for written language relative to sign language. Furthermore, cortical activity was partially modulated by age of acquisition and reading proficiency. Our results stress the important role of the basal ganglia, within the language network, in the representation of the constituent structure of language, regardless of the input modality. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. The Language Faculty - mind or brain?

    DEFF Research Database (Denmark)

    Thrane, Torben

    2009-01-01

    The paper subjects Chomsky's compound creation - the 'mind/brain' - to scrutiny. It argues that it creates a slipway for talk about the human language faculty,  such that what should properly be discussed in functional terms - what the brain does when processing language - is instead talked about...

  3. Language Choice & Global Learning Networks

    Directory of Open Access Journals (Sweden)

    Dennis Sayers

    1995-05-01

    Full Text Available How can other languages be used in conjunction with English to further intercultural and multilingual learning when teachers and students participate in computer-based global learning networks? Two portraits are presented of multilingual activities in the Orillas and I*EARN learning networks, and are discussed as examples of the principal modalities of communication employed in networking projects between distant classes. Next, an important historical precedent --the social controversy which accompanied the introduction of telephone technology at the end of the last century-- is examined in terms of its implications for language choice in contemporary classroom telecomputing projects. Finally, recommendations are offered to guide decision making concerning the role of language choice in promoting collaborative critical inquiry.

  4. Brain mechanisms in early language acquisition.

    Science.gov (United States)

    Kuhl, Patricia K

    2010-09-09

    The last decade has produced an explosion in neuroscience research examining young children's early processing of language. Noninvasive, safe functional brain measurements have now been proven feasible for use with children starting at birth. The phonetic level of language is especially accessible to experimental studies that document the innate state and the effect of learning on the brain. The neural signatures of learning at the phonetic level can be documented at a remarkably early point in development. Continuity in linguistic development from infants' earliest brain responses to phonetic stimuli is reflected in their language and prereading abilities in the second, third, and fifth year of life, a finding with theoretical and clinical impact. There is evidence that early mastery of the phonetic units of language requires learning in a social context. Neuroscience on early language learning is beginning to reveal the multiple brain systems that underlie the human language faculty. 2010 Elsevier Inc. All rights reserved.

  5. Language or Music, Mother or Mozart? Structural and Environmental Influences on Infants' Language Networks

    Science.gov (United States)

    Dehaene-Lambertz, G.; Montavont, A.; Jobert, A.; Allirol, L.; Dubois, J.; Hertz-Pannier, L.; Dehaene, S.

    2010-01-01

    Understanding how language emerged in our species calls for a detailed investigation of the initial specialization of the human brain for speech processing. Our earlier research demonstrated that an adult-like left-lateralized network of perisylvian areas is already active when infants listen to sentences in their native language, but did not…

  6. Language and Tools for Networkers

    NARCIS (Netherlands)

    Wielinga, E.; Vrolijk, M.

    2009-01-01

    The network society has a major impact on knowledge systems, and in agricultural and rural development. It has changed relationships between actors such as farmers, extension workers, researchers, policy-makers, businessmen and consumers. These changes require different language, concepts and tools

  7. Brain readiness and the nature of language.

    Science.gov (United States)

    Bouchard, Denis

    2015-01-01

    To identify the neural components that make a brain ready for language, it is important to have well defined linguistic phenotypes, to know precisely what language is. There are two central features to language: the capacity to form signs (words), and the capacity to combine them into complex structures. We must determine how the human brain enables these capacities. A sign is a link between a perceptual form and a conceptual meaning. Acoustic elements and content elements, are already brain-internal in non-human animals, but as categorical systems linked with brain-external elements. Being indexically tied to objects of the world, they cannot freely link to form signs. A crucial property of a language-ready brain is the capacity to process perceptual forms and contents offline, detached from any brain-external phenomena, so their "representations" may be linked into signs. These brain systems appear to have pleiotropic effects on a variety of phenotypic traits and not to be specifically designed for language. Syntax combines signs, so the combination of two signs operates simultaneously on their meaning and form. The operation combining the meanings long antedates its function in language: the primitive mode of predication operative in representing some information about an object. The combination of the forms is enabled by the capacity of the brain to segment vocal and visual information into discrete elements. Discrete temporal units have order and juxtaposition, and vocal units have intonation, length, and stress. These are primitive combinatorial processes. So the prior properties of the physical and conceptual elements of the sign introduce combinatoriality into the linguistic system, and from these primitive combinatorial systems derive concatenation in phonology and combination in morphosyntax. Given the nature of language, a key feature to our understanding of the language-ready brain is to be found in the mechanisms in human brains that enable the unique

  8. Brain readiness and the nature of language

    Directory of Open Access Journals (Sweden)

    Denis eBouchard

    2015-09-01

    Full Text Available To identify the neural components that make a brain ready for language, it is important to have well defined linguistic phenotypes, to know precisely what language is. There are two central features to language: the capacity to form signs (words, and the capacity to combine them into complex structures. We must determine how the human brain enables these capacities.A sign is a link between a perceptual form and a conceptual meaning. Acoustic elements and content elements, are already brain-internal in non-human animals, but as categorical systems linked with brain-external elements. Being indexically tied to objects of the world, they cannot freely link to form signs. A crucial property of a language-ready brain is the capacity to process perceptual forms and contents offline, detached from any brain-external phenomena, so their representations may be linked into signs. These brain systems appear to have pleiotropic effects on a variety of phenotypic traits and not to be specifically designed for language.Syntax combines signs, so the combination of two signs operates simultaneously on their meaning and form. The operation combining the meanings long antedates its function in language: the primitive mode of predication operative in representing some information about an object. The combination of the forms is enabled by the capacity of the brain to segment vocal and visual information into discrete elements. Discrete temporal units have order and juxtaposition, and vocal units have intonation, length, and stress. These are primitive combinatorial processes. So the prior properties of the physical and conceptual elements of the sign introduce combinatoriality into the linguistic system, and from these primitive combinatorial systems derive concatenation in phonology and combination in morphosyntax.Given the nature of language, a key feature to our understanding of the language-ready brain is to be found in the mechanisms in human brains that

  9. Shapley ratings in brain networks

    Directory of Open Access Journals (Sweden)

    Rolf Kötter

    2007-11-01

    Full Text Available Recent applications of network theory to brain networks as well as the expanding empirical databases of brain architecture spawn an interest in novel techniques for analyzing connectivity patterns in the brain. Treating individual brain structures as nodes in a directed graph model permits the application of graph theoretical concepts to the analysis of these structures within their large-scale connectivity networks. In this paper, we explore the application of concepts from graph and game theory toward this end. Specifically, we utilize the Shapley value principle, which assigns a rank to players in a coalition based upon their individual contributions to the collective profit of that coalition, to assess the contributions of individual brain structures to the graph derived from the global connectivity network. We report Shapley values for variations of a prefrontal network, as well as for a visual cortical network, which had both been extensively investigated previously. This analysis highlights particular nodes as strong or weak contributors to global connectivity. To understand the nature of their contribution, we compare the Shapley values obtained from these networks and appropriate controls to other previously described nodal measures of structural connectivity. We find a strong correlation between Shapley values and both betweenness centrality and connection density. Moreover, a stepwise multiple linear regression analysis indicates that approximately 79% of the variance in Shapley values obtained from random networks can be explained by betweenness centrality alone. Finally, we investigate the effects of local lesions on the Shapley ratings, showing that the present networks have an immense structural resistance to degradation. We discuss our results highlighting the use of such measures for characterizing the organization and functional role of brain networks.

  10. Brain, Mind and Language Functional Architectures

    OpenAIRE

    Fingelkurts, Andrew A; Fingelkurts, Alexander A; Marchetti, Giorgio

    2010-01-01

    The interaction between brain and language has been investigated by a vast amount of research and different approaches, which however do not offer a comprehensive and unified theoretical framework to analyze how brain functioning performs the mental processes we use in producing language and in understanding speech. This Special Issue addresses the need to develop such a general theoretical framework, by fostering an interaction among the various scientific disciplines and methodologies, whic...

  11. Scholastic performance and functional connectivity of brain networks in children.

    Directory of Open Access Journals (Sweden)

    Laura Chaddock-Heyman

    Full Text Available One of the keys to understanding scholastic success is to determine the neural processes involved in school performance. The present study is the first to use a whole-brain connectivity approach to explore whether functional connectivity of resting state brain networks is associated with scholastic performance in seventy-four 7- to 9-year-old children. We demonstrate that children with higher scholastic performance across reading, math and language have more integrated and interconnected resting state networks, specifically the default mode network, salience network, and frontoparietal network. To add specificity, core regions of the dorsal attention and visual networks did not relate to scholastic performance. The results extend the cognitive role of brain networks in children as well as suggest the importance of network connectivity in scholastic success.

  12. Evolution, brain, and the nature of language.

    Science.gov (United States)

    Berwick, Robert C; Friederici, Angela D; Chomsky, Noam; Bolhuis, Johan J

    2013-02-01

    Language serves as a cornerstone for human cognition, yet much about its evolution remains puzzling. Recent research on this question parallels Darwin's attempt to explain both the unity of all species and their diversity. What has emerged from this research is that the unified nature of human language arises from a shared, species-specific computational ability. This ability has identifiable correlates in the brain and has remained fixed since the origin of language approximately 100 thousand years ago. Although songbirds share with humans a vocal imitation learning ability, with a similar underlying neural organization, language is uniquely human. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. Attention shifts the language network reflecting paradigm presentation

    Directory of Open Access Journals (Sweden)

    Kathrin eKollndorfer

    2013-11-01

    Full Text Available Objectives: Functional magnetic resonance imaging (fMRI is a reliable and non-invasive method with which to localize language function in pre-surgical planning. In clinical practice, visual stimulus presentation is often difficult or impossible, due to the patient’s restricted language or attention abilities. Therefore, our aim was to investigate modality-specific differences in visual and auditory stimulus presentation.Methods: Ten healthy subjects participated in an fMRI study comprising two experiments with visual and auditory stimulus presentation. In both experiments, two language paradigms (one for language comprehension and one for language production used in clinical practice were investigated. In addition to standard data analysis by the means of the general linear model (GLM, independent component analysis (ICA was performed to achieve more detailed information on language processing networks.Results: GLM analysis revealed modality-specific brain activation for both language paradigms for the contrast visual > auditory in the area of the intraparietal sulcus and the hippocampus, two areas related to attention and working memory. Using group ICA, a language network was detected for both paradigms independent of stimulus presentation modality. The investigation of language lateralization revealed no significant variations. Visually presented stimuli further activated an attention-shift network, which could not be identified for the auditory presented language.Conclusion: The results of this study indicate that the visually presented language stimuli additionally activate an attention-shift network. These findings will provide important information for pre-surgical planning in order to preserve reading abilities after brain surgery, significantly improving surgical outcomes. Our findings suggest that the presentation modality for language paradigms should be adapted on behalf of individual indication.

  14. Neurobiology: Language By, In, Through and Across the Brain

    Science.gov (United States)

    Müller, Ralph-Axel

    Language has come to be commonly understood as something accomplished by the brain. Much scientific investigation has consequently focused in looking for language in the brain. Although it may sound intuitive, this approach suggests that language is an object located inside another object. This spatial metaphor has generated important insights into the brain sites important for language, from nineteenth century studies of brain-damaged patients to more recent and refined evidence from brain imaging.

  15. How Localized are Language Brain Areas? A Review of Brodmann Areas Involvement in Oral Language.

    Science.gov (United States)

    Ardila, Alfredo; Bernal, Byron; Rosselli, Monica

    2016-02-01

    The interest in understanding how language is "localized" in the brain has existed for centuries. Departing from seven meta-analytic studies of functional magnetic resonance imaging activity during the performance of different language activities, it is proposed here that there are two different language networks in the brain: first, a language reception/understanding system, including a "core Wernicke's area" involved in word recognition (BA21, BA22, BA41, and BA42), and a fringe or peripheral area ("extended Wernicke's area:" BA20, BA37, BA38, BA39, and BA40) involved in language associations (associating words with other information); second, a language production system ("Broca's complex:" BA44, BA45, and also BA46, BA47, partially BA6-mainly its mesial supplementary motor area-and extending toward the basal ganglia and the thalamus). This paper additionally proposes that the insula (BA13) plays a certain coordinating role in interconnecting these two brain language systems. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  16. Functional connectivity changes in the language network during stroke recovery.

    Science.gov (United States)

    Nair, Veena A; Young, Brittany M; La, Christian; Reiter, Peter; Nadkarni, Tanvi N; Song, Jie; Vergun, Svyatoslav; Addepally, Naga Saranya; Mylavarapu, Krishna; Swartz, Jennifer L; Jensen, Matthew B; Chacon, Marcus R; Sattin, Justin A; Prabhakaran, Vivek

    2015-02-01

    Several neuroimaging studies have examined language reorganization in stroke patients with aphasia. However, few studies have examined language reorganization in stroke patients without aphasia. Here, we investigated functional connectivity (FC) changes after stroke in the language network using resting-state fMRI and performance on a verbal fluency (VF) task in patients without clinically documented language deficits. Early-stage ischemic stroke patients (N = 26) (average 5 days from onset), 14 of whom were tested at a later stage (average 4.5 months from onset), 26 age-matched healthy control subjects (HCs), and 12 patients with cerebrovascular risk factors (patients at risk, PR) participated in this study. We examined FC of the language network with 23 seed regions based on a previous study. We evaluated patients' behavioral performance on a VF task and correlation between brain resting-state FC (rsFC) and behavior. Compared to HCs, early stroke patients showed significantly decreased rsFC in the language network but no difference with respect to PR. Early stroke patients showed significant differences in performance on the VF task compared to HCs but not PR. Late-stage patients compared to HCs and PR showed no differences in brain rsFC in the language network and significantly stronger connections compared to early-stage patients. Behavioral differences persisted in the late stage compared to HCs. Change in specific connection strengths correlated with changes in behavior from early to late stage. These results show decreased rsFC in the language network and verbal fluency deficits in early stroke patients without clinically documented language deficits.

  17. The Brain in Singing and Language

    Science.gov (United States)

    Trollinger, Valerie L.

    2010-01-01

    This article summarizes currently available brain research concerning relationships between singing and language development. Although this is a new field of investigation, there are findings that are applicable to general music teaching classroom. These findings are presented along with suggestions about how to apply them to teaching music.

  18. Early bilingualism, language attainment, and brain development.

    Science.gov (United States)

    Berken, Jonathan A; Gracco, Vincent L; Klein, Denise

    2017-04-01

    The brain demonstrates a remarkable capacity to undergo structural and functional change in response to experience throughout the lifespan. Evidence suggests that, in many domains of skill acquisition, the manifestation of this neuroplasticity depends on the age at which learning begins. The fact that most skills are acquired late in childhood or in adulthood has proven to be a limitation in studies aimed at determining the relationship between age of acquisition and brain plasticity. Bilingualism, however, provides an optimal model for discerning differences in how the brain wires when a skill is acquired from birth, when the brain circuitry for language is being constructed, versus later in life, when the pathways subserving the first language are already well developed. This review examines some of the existing knowledge about optimal periods in language development, with particular attention to the attainment of native-like phonology. It focuses on the differences in brain structure and function between simultaneous and sequential bilinguals and the compensatory mechanisms employed when bilingualism is achieved later in life, based on evidence from studies using a variety of neuroimaging modalities, including positron emission tomography (PET), task-based and resting-state functional magnetic resonance imaging (fMRI), and structural MRI. The discussion concludes with the presentation of recent neuroimaging studies that explore the concept of nested optimal periods in language development and the different neural paths to language proficiency taken by simultaneous and sequential bilinguals, with extrapolation to general notions of the relationship between age of acquisition and ultimate skill performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Altered functional connectivity of the language network in ASD: Role of classical language areas and cerebellum

    Directory of Open Access Journals (Sweden)

    Marjolein Verly

    2014-01-01

    Full Text Available The development of language, social interaction and communicative skills is remarkably different in the child with autism spectrum disorder (ASD. Atypical brain connectivity has frequently been reported in this patient population. However, the neural correlates underlying their disrupted language development and functioning are still poorly understood. Using resting state fMRI, we investigated the functional connectivity properties of the language network in a group of ASD patients with clear comorbid language impairment (ASD-LI; N = 19 and compared them to the language related connectivity properties of 23 age-matched typically developing children. A verb generation task was used to determine language components commonly active in both groups. Eight joint language components were identified and subsequently used as seeds in a resting state analysis. Interestingly, both the interregional and the seed-based whole brain connectivity analysis showed preserved connectivity between the classical intrahemispheric language centers, Wernicke's and Broca's areas. In contrast however, a marked loss of functional connectivity was found between the right cerebellar region and the supratentorial regulatory language areas. Also, the connectivity between the interhemispheric Broca regions and modulatory control dorsolateral prefrontal region was found to be decreased. This disruption of normal modulatory control and automation function by the cerebellum may underlie the abnormal language function in children with ASD-LI.

  20. Cerebro, lenguaje y comunicacion (Brain, Language, and Communication).

    Science.gov (United States)

    Strejilevich, Leonardo

    1978-01-01

    Discusses the relationship between the brain, language, and communication in the following sections: (1) combining words, (2) language as a system, (3) language as a function of the brain, (4) the science of communication, and (5) language as a social institution. (NCR)

  1. Early Language Learning and the Social Brain.

    Science.gov (United States)

    Kuhl, Patricia K

    2014-01-01

    Explaining how every typically developing child acquires language is one of the grand challenges of cognitive neuroscience. Historically, language learning provoked classic debates about the contributions of innately specialized as opposed to general learning mechanisms. Now, new data are being brought to bear from studies that employ magnetoencephalograph (MEG), electroencephalograph (EEG), magnetic resonance imaging (MRI), and diffusion tensor imaging (DTI) studies on young children. These studies examine the patterns of association between brain and behavioral measures. The resulting data offer both expected results and surprises that are altering theory. As we uncover what it means to be human through the lens of young children, and their ability to speak, what we learn will not only inform theories of human development, but also lead to the discovery of neural biomarkers, early in life, that indicate risk for language impairment and allow early intervention for children with developmental disabilities involving language. Copyright © 2014 Cold Spring Harbor Laboratory Press; all rights reserved.

  2. Smart Cities and Languages: The Language Network

    Directory of Open Access Journals (Sweden)

    Andrea Gobbi

    2013-05-01

    Full Text Available This paper intends to analyze the potential of smart cities from a linguistic perspective, with particular attention towards aspects such as second language acquisition (SLA, social inclusion and innovation, but also positive influences on sectors such as tourism and commerce. After an introduction of the theoretical foundations, the possible developing scenarios will be taken into consideration and analyzed more in detail.

  3. Using the Network Description Language in Optical Networks

    NARCIS (Netherlands)

    van der Ham, J.J.; Grosso, P.; van der Pol, R.; Toonk, A.; de Laat, C.T.A.M.

    2007-01-01

    Current research networks allow end users to build their own application-specific connections (lightpaths) and Optical Private Networks (OPNs). This requires a clear communication between the requesting application and the network. The Network Description Language (NDL) is a vocabulary designed to

  4. Brain network activity in monolingual and bilingual older adults.

    Science.gov (United States)

    Grady, Cheryl L; Luk, Gigi; Craik, Fergus I M; Bialystok, Ellen

    2015-01-01

    Bilingual older adults typically have better performance on tasks of executive control (EC) than do their monolingual peers, but differences in brain activity due to language experience are not well understood. Based on studies showing a relation between the dynamic range of brain network activity and performance on EC tasks, we hypothesized that life-long bilingual older adults would show increased functional connectivity relative to monolinguals in networks related to EC. We assessed intrinsic functional connectivity and modulation of activity in task vs. fixation periods in two brain networks that are active when EC is engaged, the frontoparietal control network (FPC) and the salience network (SLN). We also examined the default mode network (DMN), which influences behavior through reduced activity during tasks. We found stronger intrinsic functional connectivity in the FPC and DMN in bilinguals than in monolinguals. Although there were no group differences in the modulation of activity across tasks and fixation, bilinguals showed stronger correlations than monolinguals between intrinsic connectivity in the FPC and task-related increases of activity in prefrontal and parietal regions. This bilingual difference in network connectivity suggests that language experience begun in childhood and continued throughout adulthood influences brain networks in ways that may provide benefits in later life. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Brain networks of social comparison.

    Science.gov (United States)

    Kedia, Gayannée; Lindner, Michael; Mussweiler, Thomas; Ihssen, Niklas; Linden, David E J

    2013-03-27

    Social comparison, that is, the process of comparing oneself to other people, is a ubiquitous social cognitive mechanism; however, so far its neural correlates have remained unknown. The present study tested the hypothesis that social comparisons are supported by partly dissociated networks, depending on whether the dimension under comparison concerns a physical or a psychological attribute. We measured brain activity with functional MRI, whereas participants were comparing their own height or intelligence to that of individuals they personally know. Height comparisons were associated with higher activity in a frontoparietal network involved in spatial and numerical cognition. Conversely, intelligence comparisons recruited a network of midline areas that have been previously implicated in the attribution of mental states to oneself and others (Theory of mind). These findings suggest that social comparisons rely on diverse domain-specific mechanisms rather than on one unitary process.

  6. Approaching human language with complex networks

    Science.gov (United States)

    Cong, Jin; Liu, Haitao

    2014-12-01

    The interest in modeling and analyzing human language with complex networks is on the rise in recent years and a considerable body of research in this area has already been accumulated. We survey three major lines of linguistic research from the complex network approach: 1) characterization of human language as a multi-level system with complex network analysis; 2) linguistic typological research with the application of linguistic networks and their quantitative measures; and 3) relationships between the system-level complexity of human language (determined by the topology of linguistic networks) and microscopic linguistic (e.g., syntactic) features (as the traditional concern of linguistics). We show that the models and quantitative tools of complex networks, when exploited properly, can constitute an operational methodology for linguistic inquiry, which contributes to the understanding of human language and the development of linguistics. We conclude our review with suggestions for future linguistic research from the complex network approach: 1) relationships between the system-level complexity of human language and microscopic linguistic features; 2) expansion of research scope from the global properties to other levels of granularity of linguistic networks; and 3) combination of linguistic network analysis with other quantitative studies of language (such as quantitative linguistics).

  7. A European Languages Virtual Network Proposal

    Science.gov (United States)

    García-Peñalvo, Francisco José; González-González, Juan Carlos; Murray, Maria

    ELVIN (European Languages Virtual Network) is a European Union (EU) Lifelong Learning Programme Project aimed at creating an informal social network to support and facilitate language learning. The ELVIN project aims to research and develop the connection between social networks, professional profiles and language learning in an informal educational context. At the core of the ELVIN project, there will be a web 2.0 social networking platform that connects employees/students for language practice based on their own professional/academic needs and abilities, using all relevant technologies. The ELVIN remit involves the examination of both methodological and technological issues inherent in achieving a social-based learning platform that provides the user with their own customized Personal Learning Environment for EU language acquisition. ELVIN started in November 2009 and this paper presents the project aims and objectives as well as the development and implementation of the web platform.

  8. Mapping distributed brain function and networks with diffuse optical tomography

    Science.gov (United States)

    Eggebrecht, Adam T.; Ferradal, Silvina L.; Robichaux-Viehoever, Amy; Hassanpour, Mahlega S.; Dehghani, Hamid; Snyder, Abraham Z.; Hershey, Tamara; Culver, Joseph P.

    2014-06-01

    Mapping of human brain function has revolutionized systems neuroscience. However, traditional functional neuroimaging by positron emission tomography or functional magnetic resonance imaging cannot be used when applications require portability, or are contraindicated because of ionizing radiation (positron emission tomography) or implanted metal (functional magnetic resonance imaging). Optical neuroimaging offers a non-invasive alternative that is radiation free and compatible with implanted metal and electronic devices (for example, pacemakers). However, optical imaging technology has heretofore lacked the combination of spatial resolution and wide field of view sufficient to map distributed brain functions. Here, we present a high-density diffuse optical tomography imaging array that can map higher-order, distributed brain function. The system was tested by imaging four hierarchical language tasks and multiple resting-state networks including the dorsal attention and default mode networks. Finally, we imaged brain function in patients with Parkinson's disease and implanted deep brain stimulators that preclude functional magnetic resonance imaging.

  9. Network Basic Language Translation System: Security Infrastructure

    National Research Council Canada - National Science Library

    Mittrick, Mark R

    2007-01-01

    .... The Network Basic Language Translation System (NetBLTS) was proposed and accepted as part of the U.S. Army Research Laboratory's offering of initiatives within the Horizontal Fusion portfolio in 2003...

  10. Language and the newborn brain: Does prenatal language experience shape the neonate neural response to speech?

    OpenAIRE

    Lillian eMay; Krista eByers-Heinlein; Judit eGervain; Janet F Werker

    2011-01-01

    Previous research has shown that by the time of birth, the neonate brain responds specially to the native language when compared to acoustically similar non-language stimuli. In the current study, we use Near Infrared Spectroscopy to ask how prenatal language experience might shape the brain response to language in newborn infants. To do so, we examine the neural response of neonates when listening to familiar versus unfamiliar language, as well as to non-linguistic backwards language. Twenty...

  11. Brain basis of communicative actions in language.

    Science.gov (United States)

    Egorova, Natalia; Shtyrov, Yury; Pulvermüller, Friedemann

    2016-01-15

    Although language is a key tool for communication in social interaction, most studies in the neuroscience of language have focused on language structures such as words and sentences. Here, the neural correlates of speech acts, that is, the actions performed by using language, were investigated with functional magnetic resonance imaging (fMRI). Participants were shown videos, in which the same critical utterances were used in different communicative contexts, to Name objects, or to Request them from communication partners. Understanding of critical utterances as Requests was accompanied by activation in bilateral premotor, left inferior frontal and temporo-parietal cortical areas known to support action-related and social interactive knowledge. Naming, however, activated the left angular gyrus implicated in linking information about word forms and related reference objects mentioned in critical utterances. These findings show that understanding of utterances as different communicative actions is reflected in distinct brain activation patterns, and thus suggest different neural substrates for different speech act types. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  12. Brain network clustering with information flow motifs

    NARCIS (Netherlands)

    Märtens, M.; Meier, J.M.; Hillebrand, Arjan; Tewarie, Prejaas; Van Mieghem, P.F.A.

    2017-01-01

    Recent work has revealed frequency-dependent global patterns of information flow by a network analysis of magnetoencephalography data of the human brain. However, it is unknown which properties on a small subgraph-scale of those functional brain networks are dominant at different frequencies bands.

  13. Schizophrenia and abnormal brain network hubs.

    Science.gov (United States)

    Rubinov, Mikail; Bullmore, Ed

    2013-09-01

    Schizophrenia is a heterogeneous psychiatric disorder of unknown cause or characteristic pathology. Clinical neuroscientists increasingly postulate that schizophrenia is a disorder of brain network organization. In this article we discuss the conceptual framework of this dysconnection hypothesis, describe the predominant methodological paradigm for testing this hypothesis, and review recent evidence for disruption of central/hub brain regions, as a promising example of this hypothesis. We summarize studies of brain hubs in large-scale structural and functional brain networks and find strong evidence for network abnormalities of prefrontal hubs, and moderate evidence for network abnormalities of limbic, temporal, and parietal hubs. Future studies are needed to differentiate network dysfunction from previously observed gray- and white-matter abnormalities of these hubs, and to link endogenous network dysfunction phenotypes with perceptual, behavioral, and cognitive clinical phenotypes of schizophrenia.

  14. Network hubs in the human brain.

    Science.gov (United States)

    van den Heuvel, Martijn P; Sporns, Olaf

    2013-12-01

    Virtually all domains of cognitive function require the integration of distributed neural activity. Network analysis of human brain connectivity has consistently identified sets of regions that are critically important for enabling efficient neuronal signaling and communication. The central embedding of these candidate 'brain hubs' in anatomical networks supports their diverse functional roles across a broad range of cognitive tasks and widespread dynamic coupling within and across functional networks. The high level of centrality of brain hubs also renders them points of vulnerability that are susceptible to disconnection and dysfunction in brain disorders. Combining data from numerous empirical and computational studies, network approaches strongly suggest that brain hubs play important roles in information integration underpinning numerous aspects of complex cognitive function. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Scaling in topological properties of brain networks

    NARCIS (Netherlands)

    Singh, S.S.; Khundrakpam, B.S.; Reid, A.T.; Lewis, J.D.; Evans, A.C.; Ishrat, R.; Sharma, B.I.; Singh, R.K.B.

    2016-01-01

    The organization in brain networks shows highly modular features with weak inter-modular interaction. The topology of the networks involves emergence of modules and sub-modules at different levels of constitution governed by fractal laws that are signatures of self-organization in complex networks.

  16. Lesion characteristics driving right-hemispheric language reorganization in congenital left-hemispheric brain damage.

    Science.gov (United States)

    Lidzba, Karen; de Haan, Bianca; Wilke, Marko; Krägeloh-Mann, Ingeborg; Staudt, Martin

    2017-10-01

    Pre- or perinatally acquired ("congenital") left-hemispheric brain lesions can be compensated for by reorganizing language into homotopic brain regions in the right hemisphere. Language comprehension may be hemispherically dissociated from language production. We investigated the lesion characteristics driving inter-hemispheric reorganization of language comprehension and language production in 19 patients (7-32years; eight females) with congenital left-hemispheric brain lesions (periventricular lesions [n=11] and middle cerebral artery infarctions [n=8]) by fMRI. 16/17 patients demonstrated reorganized language production, while 7/19 patients had reorganized language comprehension. Lesions to the insular cortex and the temporo-parietal junction (predominantly supramarginal gyrus) were significantly more common in patients in whom both, language production and comprehension were reorganized. These areas belong to the dorsal stream of the language network, participating in the auditory-motor integration of language. Our data suggest that the integrity of this stream might be crucial for a normal left-lateralized language development. Copyright © 2017. Published by Elsevier Inc.

  17. Dynamic brain architectures in local brain activity and functional network efficiency associate with efficient reading in bilinguals.

    Science.gov (United States)

    Feng, Gangyi; Chen, Hsuan-Chih; Zhu, Zude; He, Yong; Wang, Suiping

    2015-10-01

    The human brain is organized as a dynamic network, in which both regional brain activity and inter-regional connectivity support high-level cognitive processes, such as reading. However, it is still largely unknown how the functional brain network organizes to enable fast and effortless reading processing in the native language (L1) but not in a non-proficient second language (L2), and whether the mechanisms underlying local activity are associated with connectivity dynamics in large-scale brain networks. In the present study, we combined activation-based and multivariate graph-theory analysis with functional magnetic resonance imaging data to address these questions. Chinese-English unbalanced bilinguals read narratives for comprehension in Chinese (L1) and in English (L2). Compared with L2, reading in L1 evoked greater brain activation and recruited a more globally efficient but less clustered network organization. Regions with both increased network efficiency and enhanced brain activation in L1 reading were mostly located in the fronto-temporal reading-related network (RN), whereas regions with decreased global network efficiency, increased clustering, and more deactivation in L2 reading were identified in the default mode network (DMN). Moreover, functional network efficiency was closely associated with local brain activation, and such associations were also modulated by reading efficiency in the two languages. Our results demonstrate that an economical and integrative brain network topology is associated with efficient reading, and further reveal a dynamic association between network efficiency and local activation for both RN and DMN. These findings underscore the importance of considering interregional connectivity when interpreting local BOLD signal changes in bilingual reading. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Neural network approaches for noisy language modeling.

    Science.gov (United States)

    Li, Jun; Ouazzane, Karim; Kazemian, Hassan B; Afzal, Muhammad Sajid

    2013-11-01

    Text entry from people is not only grammatical and distinct, but also noisy. For example, a user's typing stream contains all the information about the user's interaction with computer using a QWERTY keyboard, which may include the user's typing mistakes as well as specific vocabulary, typing habit, and typing performance. In particular, these features are obvious in disabled users' typing streams. This paper proposes a new concept called noisy language modeling by further developing information theory and applies neural networks to one of its specific application-typing stream. This paper experimentally uses a neural network approach to analyze the disabled users' typing streams both in general and specific ways to identify their typing behaviors and subsequently, to make typing predictions and typing corrections. In this paper, a focused time-delay neural network (FTDNN) language model, a time gap model, a prediction model based on time gap, and a probabilistic neural network model (PNN) are developed. A 38% first hitting rate (HR) and a 53% first three HR in symbol prediction are obtained based on the analysis of a user's typing history through the FTDNN language modeling, while the modeling results using the time gap prediction model and the PNN model demonstrate that the correction rates lie predominantly in between 65% and 90% with the current testing samples, and 70% of all test scores above basic correction rates, respectively. The modeling process demonstrates that a neural network is a suitable and robust language modeling tool to analyze the noisy language stream. The research also paves the way for practical application development in areas such as informational analysis, text prediction, and error correction by providing a theoretical basis of neural network approaches for noisy language modeling.

  19. Defining nodes in complex brain networks

    Directory of Open Access Journals (Sweden)

    Matthew Lawrence Stanley

    2013-11-01

    Full Text Available Network science holds great promise for expanding our understanding of the human brain in health, disease, development, and aging. Network analyses are quickly becoming the method of choice for analyzing functional MRI data. However, many technical issues have yet to be confronted in order to optimize results. One particular issue that remains controversial in functional brain network analyses is the definition of a network node. In functional brain networks a node represents some predefined collection of brain tissue, and an edge measures the functional connectivity between pairs of nodes. The characteristics of a node, chosen by the researcher, vary considerably in the literature. This manuscript reviews the current state of the art based on published manuscripts and highlights the strengths and weaknesses of three main methods for defining nodes. Voxel-wise networks are constructed by assigning a node to each, equally sized brain area (voxel. The fMRI time-series recorded from each voxel is then used to create the functional network. Anatomical methods utilize atlases to define the nodes based on brain structure. The fMRI time-series from all voxels within the anatomical area are averaged and subsequently used to generate the network. Functional activation methods rely on data from traditional fMRI activation studies, often from databases, to identify network nodes. Such methods identify the peaks or centers of mass from activation maps to determine the location of the nodes. Small (~10-20 millimeter diameter spheres located at the coordinates of the activation foci are then applied to the data being used in the network analysis. The fMRI time-series from all voxels in the sphere are then averaged, and the resultant time series is used to generate the network. We attempt to clarify the discussion and move the study of complex brain networks forward. While the correct method to be used remains an open, possibly unsolvable question that

  20. Monitoring Different Phonological Parameters of Sign Language Engages the Same Cortical Language Network but Distinctive Perceptual Ones.

    Science.gov (United States)

    Cardin, Velia; Orfanidou, Eleni; Kästner, Lena; Rönnberg, Jerker; Woll, Bencie; Capek, Cheryl M; Rudner, Mary

    2016-01-01

    The study of signed languages allows the dissociation of sensorimotor and cognitive neural components of the language signal. Here we investigated the neurocognitive processes underlying the monitoring of two phonological parameters of sign languages: handshape and location. Our goal was to determine if brain regions processing sensorimotor characteristics of different phonological parameters of sign languages were also involved in phonological processing, with their activity being modulated by the linguistic content of manual actions. We conducted an fMRI experiment using manual actions varying in phonological structure and semantics: (1) signs of a familiar sign language (British Sign Language), (2) signs of an unfamiliar sign language (Swedish Sign Language), and (3) invented nonsigns that violate the phonological rules of British Sign Language and Swedish Sign Language or consist of nonoccurring combinations of phonological parameters. Three groups of participants were tested: deaf native signers, deaf nonsigners, and hearing nonsigners. Results show that the linguistic processing of different phonological parameters of sign language is independent of the sensorimotor characteristics of the language signal. Handshape and location were processed by different perceptual and task-related brain networks but recruited the same language areas. The semantic content of the stimuli did not influence this process, but phonological structure did, with nonsigns being associated with longer RTs and stronger activations in an action observation network in all participants and in the supramarginal gyrus exclusively in deaf signers. These results suggest higher processing demands for stimuli that contravene the phonological rules of a signed language, independently of previous knowledge of signed languages. We suggest that the phonological characteristics of a language may arise as a consequence of more efficient neural processing for its perception and production.

  1. Experience-Dependent Brain Development as a Key to Understanding the Language System.

    Science.gov (United States)

    Westermann, Gert

    2016-04-01

    An influential view of the nature of the language system is that of an evolved biological system in which a set of rules is combined with a lexicon that contains the words of the language together with a representation of their context. Alternative views, usually based on connectionist modeling, attempt to explain the structure of language on the basis of complex associative processes. Here, I put forward a third view that stresses experience-dependent structural development of the brain circuits supporting language as a core principle of the organization of the language system. In this view, embodied in a recent neuroconstructivist neural network of past tense development and processing, initial domain-general predispositions enable the development of functionally specialized brain structures through interactions between experience-dependent brain development and statistical learning in a structured environment. Together, these processes shape a biological adult language system that appears to separate into distinct mechanism for processing rules and exceptions, whereas in reality those subsystems co-develop and interact closely. This view puts experience-dependent brain development in response to a specific language environment at the heart of understanding not only language development but adult language processing as well. Copyright © 2016 Cognitive Science Society, Inc.

  2. Brain network science needs to become predictive. Comment on “Understanding brain networks and brain organization” by Luiz Pessoa

    Science.gov (United States)

    Hilgetag, Claus C.; von Luxburg, Ulrike

    2014-09-01

    In his thought-provoking review of current concepts in neuroscience, Pessoa [1] addresses the ongoing paradigm shift of the field, in which the perspective has moved from individual nodes to distributed networks in order to account for distributed brain function. Within this perspective, Pessoa describes diverse aspects and topological features of brain networks that are potentially relevant for brain function. As he notes, however, the shift to networks does not solve all problems of linking brain function to structure.

  3. Multilayer motif analysis of brain networks

    Science.gov (United States)

    Battiston, Federico; Nicosia, Vincenzo; Chavez, Mario; Latora, Vito

    2017-04-01

    In the last decade, network science has shed new light both on the structural (anatomical) and on the functional (correlations in the activity) connectivity among the different areas of the human brain. The analysis of brain networks has made possible to detect the central areas of a neural system and to identify its building blocks by looking at overabundant small subgraphs, known as motifs. However, network analysis of the brain has so far mainly focused on anatomical and functional networks as separate entities. The recently developed mathematical framework of multi-layer networks allows us to perform an analysis of the human brain where the structural and functional layers are considered together. In this work, we describe how to classify the subgraphs of a multiplex network, and we extend the motif analysis to networks with an arbitrary number of layers. We then extract multi-layer motifs in brain networks of healthy subjects by considering networks with two layers, anatomical and functional, respectively, obtained from diffusion and functional magnetic resonance imaging. Results indicate that subgraphs in which the presence of a physical connection between brain areas (links at the structural layer) coexists with a non-trivial positive correlation in their activities are statistically overabundant. Finally, we investigate the existence of a reinforcement mechanism between the two layers by looking at how the probability to find a link in one layer depends on the intensity of the connection in the other one. Showing that functional connectivity is non-trivially constrained by the underlying anatomical network, our work contributes to a better understanding of the interplay between the structure and function in the human brain.

  4. An adaptive complex network model for brain functional networks.

    Directory of Open Access Journals (Sweden)

    Ignacio J Gomez Portillo

    Full Text Available Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution.

  5. Study of functional brain imaging for bilingual language cognition

    International Nuclear Information System (INIS)

    Sun Da

    2008-01-01

    Bilingual and multilingual brain studies of language recognition is an interdisciplinary subject which needs to identify different levels involved in the neural representation of languages, such as neuroanatomical, neurofunctional, biochemical, psychological and linguistic levels. Furthermore, specific factor's such as age, manner of acquisition and environmental factors seem to affect the neural representation. Functional brain imaging, such as PET, SPECT and functional MRI can explore the neurolinguistics representation of bilingualism in the brain in subjects, and elucidate the neuronal mechanisms of bilingual language processing. Functional imaging methods show differences in the pattern of cerebral activation associated with a second language compared with the subject's native language. It shows that verbal memory processing in two unrelated languages is mediated by a common neural system with some distinct cortical areas. The different patterns of activation differ according to the language used. It also could be ascribed either to age of acquisition or to proficiency level. And attained proficiency is more important than age of acquisition as a determinant of the cortical representation of the second language. The study used PET and SPECT shows that sign and spoken language seem to be localized in the same brain areas, and elicit similar regional cerebral blood flow patterns. But for sign language perception, the functional anatomy overlaps that of language processing contain both auditory and visual components. And the sign language is dependent on spatial information too. (authors)

  6. A comparison of brain activity associated with language production in brain tumor patients with left and right sided language laterality

    NARCIS (Netherlands)

    Jansma, J. M.; Ramsey, N.; Rutten, G.J.M.

    2015-01-01

    Aim. Language dominance is an important factor for clinical decision making in brain tumor surgery. Functional MM can provide detailed information about the organization of language in the brain. One often used measure derived from fMRI data is the laterality index (LI). The LI is typically based on

  7. Sparse brain network using penalized linear regression

    Science.gov (United States)

    Lee, Hyekyoung; Lee, Dong Soo; Kang, Hyejin; Kim, Boong-Nyun; Chung, Moo K.

    2011-03-01

    Sparse partial correlation is a useful connectivity measure for brain networks when it is difficult to compute the exact partial correlation in the small-n large-p setting. In this paper, we formulate the problem of estimating partial correlation as a sparse linear regression with a l1-norm penalty. The method is applied to brain network consisting of parcellated regions of interest (ROIs), which are obtained from FDG-PET images of the autism spectrum disorder (ASD) children and the pediatric control (PedCon) subjects. To validate the results, we check their reproducibilities of the obtained brain networks by the leave-one-out cross validation and compare the clustered structures derived from the brain networks of ASD and PedCon.

  8. Brain rhythms reveal a hierarchical network organization.

    Directory of Open Access Journals (Sweden)

    G Karl Steinke

    2011-10-01

    Full Text Available Recordings of ongoing neural activity with EEG and MEG exhibit oscillations of specific frequencies over a non-oscillatory background. The oscillations appear in the power spectrum as a collection of frequency bands that are evenly spaced on a logarithmic scale, thereby preventing mutual entrainment and cross-talk. Over the last few years, experimental, computational and theoretical studies have made substantial progress on our understanding of the biophysical mechanisms underlying the generation of network oscillations and their interactions, with emphasis on the role of neuronal synchronization. In this paper we ask a very different question. Rather than investigating how brain rhythms emerge, or whether they are necessary for neural function, we focus on what they tell us about functional brain connectivity. We hypothesized that if we were able to construct abstract networks, or "virtual brains", whose dynamics were similar to EEG/MEG recordings, those networks would share structural features among themselves, and also with real brains. Applying mathematical techniques for inverse problems, we have reverse-engineered network architectures that generate characteristic dynamics of actual brains, including spindles and sharp waves, which appear in the power spectrum as frequency bands superimposed on a non-oscillatory background dominated by low frequencies. We show that all reconstructed networks display similar topological features (e.g. structural motifs and dynamics. We have also reverse-engineered putative diseased brains (epileptic and schizophrenic, in which the oscillatory activity is altered in different ways, as reported in clinical studies. These reconstructed networks show consistent alterations of functional connectivity and dynamics. In particular, we show that the complexity of the network, quantified as proposed by Tononi, Sporns and Edelman, is a good indicator of brain fitness, since virtual brains modeling diseased states

  9. Executive and Language Control in the Multilingual Brain

    Directory of Open Access Journals (Sweden)

    Anthony Pak-Hin Kong

    2014-01-01

    Full Text Available Neuroimaging studies suggest that the neural network involved in language control may not be specific to bi-/multilingualism but is part of a domain-general executive control system. We report a trilingual case of a Cantonese (L1, English (L2, and Mandarin (L3 speaker, Dr. T, who sustained a brain injury at the age of 77 causing lesions in the left frontal lobe and in the left temporo-parietal areas resulting in fluent aphasia. Dr. T’s executive functions were impaired according to a modified version of the Stroop color-word test and the Wisconsin Card Sorting Test performance was characterized by frequent perseveration errors. Dr. T demonstrated pathological language switching and mixing across her three languages. Code switching in Cantonese was more prominent in discourse production than confrontation naming. Our case suggests that voluntary control of spoken word production in trilingual speakers shares neural substrata in the frontobasal ganglia system with domain-general executive control mechanisms. One prediction is that lesions to such a system would give rise to both pathological switching and impairments of executive functions in trilingual speakers.

  10. Executive and language control in the multilingual brain.

    Science.gov (United States)

    Kong, Anthony Pak-Hin; Abutalebi, Jubin; Lam, Karen Sze-Yan; Weekes, Brendan

    2014-01-01

    Neuroimaging studies suggest that the neural network involved in language control may not be specific to bi-/multilingualism but is part of a domain-general executive control system. We report a trilingual case of a Cantonese (L1), English (L2), and Mandarin (L3) speaker, Dr. T, who sustained a brain injury at the age of 77 causing lesions in the left frontal lobe and in the left temporo-parietal areas resulting in fluent aphasia. Dr. T's executive functions were impaired according to a modified version of the Stroop color-word test and the Wisconsin Card Sorting Test performance was characterized by frequent perseveration errors. Dr. T demonstrated pathological language switching and mixing across her three languages. Code switching in Cantonese was more prominent in discourse production than confrontation naming. Our case suggests that voluntary control of spoken word production in trilingual speakers shares neural substrata in the frontobasal ganglia system with domain-general executive control mechanisms. One prediction is that lesions to such a system would give rise to both pathological switching and impairments of executive functions in trilingual speakers.

  11. Connectionist natural language parsing with BrainC

    Science.gov (United States)

    Mueller, Adrian; Zell, Andreas

    1991-08-01

    A close examination of pure neural parsers shows that they either could not guarantee the correctness of their derivations or had to hard-code seriality into the structure of the net. The authors therefore decided to use a hybrid architecture, consisting of a serial parsing algorithm and a trainable net. The system fulfills the following design goals: (1) parsing of sentences without length restriction, (2) soundness and completeness for any context-free language, and (3) learning the applicability of parsing rules with a neural network to increase the efficiency of the whole system. BrainC (backtracktacking and backpropagation in C) combines the well- known shift-reduce parsing technique with backtracking with a backpropagation network to learn and represent typical structures of the trained natural language grammars. The system has been implemented as a subsystem of the Rochester Connectionist Simulator (RCS) on SUN workstations and was tested with several grammars for English and German. The design of the system and then the results are discussed.

  12. Hubs in the human fetal brain network

    NARCIS (Netherlands)

    van den Heuvel, M.I.; Turk, E.; Manning, J.H.; Hect, J.; Hernandez-Andrade⁠, E.; Hassan, S.S.; Romero, R.; van den Heuvel, M.P.

    2018-01-01

    Advances in neuroimaging and network analyses have lead to discovery of highly connected regions, or hubs, in the connectional architecture of the human brain. Whether these hubs emerge as networks begin to form in utero, has yet to be examined. The current study addresses this question and aims to

  13. Brain Networks of Explicit and Implicit Learning

    Science.gov (United States)

    Yang, Jing; Li, Ping

    2012-01-01

    Are explicit versus implicit learning mechanisms reflected in the brain as distinct neural structures, as previous research indicates, or are they distinguished by brain networks that involve overlapping systems with differential connectivity? In this functional MRI study we examined the neural correlates of explicit and implicit learning of artificial grammar sequences. Using effective connectivity analyses we found that brain networks of different connectivity underlie the two types of learning: while both processes involve activation in a set of cortical and subcortical structures, explicit learners engage a network that uses the insula as a key mediator whereas implicit learners evoke a direct frontal-striatal network. Individual differences in working memory also differentially impact the two types of sequence learning. PMID:22952624

  14. Topological isomorphisms of human brain and financial market networks.

    Science.gov (United States)

    Vértes, Petra E; Nicol, Ruth M; Chapman, Sandra C; Watkins, Nicholas W; Robertson, Duncan A; Bullmore, Edward T

    2011-01-01

    Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets - the time series of 90 stocks from the New York stock exchange over a 3-year period, and the fMRI-derived time series acquired from 90 brain regions over the course of a 10-min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties. Both the human brain and the market networks were non-random, small-world, modular, hierarchical systems with fat-tailed degree distributions indicating the presence of highly connected hubs. These properties could not be trivially explained by the univariate time series statistics of stock price returns. This degree of topological isomorphism suggests that brains and markets can be regarded broadly as members of the same family of networks. The two systems, however, were not topologically identical. The financial market was more efficient and more modular - more highly optimized for information processing - than the brain networks; but also less robust to systemic disintegration as a result of hub deletion. We conclude that the conceptual connections between brains and markets are not merely metaphorical; rather these two information processing systems can be rigorously compared in the same mathematical language and turn out often to share important topological properties in common to some degree. There will be interesting scientific arbitrage opportunities in further work at the graph-theoretically mediated interface between systems neuroscience and the statistical physics of financial markets.

  15. Topological isomorphisms of human brain and financial market networks

    Directory of Open Access Journals (Sweden)

    Petra E Vértes

    2011-09-01

    Full Text Available Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets - the timeseries of 90 stocks from the New York Stock Exchange over a three-year period, and the fMRI-derived timeseries acquired from 90 brain regions over the course of a 10 min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties. Both the human brain and the market networks were non-random, small-world, modular, hierarchical systems with fat-tailed degree distributions indicating the presence of highly connected hubs. These properties could not be trivially explained by the univariate time series statistics of stock price returns. This degree of topological isomorphism suggests that brains and markets can be regarded broadly as members of the same family of networks. The two systems, however, were not topologically identical. The financial market was more efficient and more modular - more highly optimised for information processing - than the brain networks; but also less robust to systemic disintegration as a result of hub deletion. We conclude that the conceptual connections between brains and markets are not merely metaphorical; rather these two information processing systems can be rigorously compared in the same mathematical language and turn out often to share important topological properties in common to some degree. There will be interesting scientific arbitrage opportunities in further work at the graph theoretically-mediated interface between systems neuroscience and the statistical physics of financial markets.

  16. Language Views on Social Networking Sites for Language Learning: The Case of Busuu

    Science.gov (United States)

    Álvarez Valencia, José Aldemar

    2016-01-01

    Social networking has compelled the area of computer-assisted language learning (CALL) to expand its research palette and account for new virtual ecologies that afford language learning and socialization. This study focuses on Busuu, a social networking site for language learning (SNSLL), and analyzes the views of language that are enacted through…

  17. Hebrew brain vs. English brain: Language modulates the way it is processed

    OpenAIRE

    Bick, Atira S.; Goelman, Gadi; Frost, Ram

    2010-01-01

    Is language processing universal? How do the specific properties of each language influence the way it is processed? In this study we compare the neural correlates of morphological processing in Hebrew – a Semitic language with a rich and systematic morphology, to those revealed in English – an Indo-European language with a linear morphology. Using fMRI we show that while in the bilingual brain both languages involve a common neural circuitry in processing morphological structure, this activa...

  18. Interaction between lexical and grammatical language systems in the brain

    Science.gov (United States)

    Ardila, Alfredo

    2012-06-01

    This review concentrates on two different language dimensions: lexical/semantic and grammatical. This distinction between a lexical/semantic system and a grammatical system is well known in linguistics, but in cognitive neurosciences it has been obscured by the assumption that there are several forms of language disturbances associated with focal brain damage and hence language includes a diversity of functions (phoneme discrimination, lexical memory, grammar, repetition, language initiation ability, etc.), each one associated with the activity of a specific brain area. The clinical observation of patients with cerebral pathology shows that there are indeed only two different forms of language disturbances (disturbances in the lexical/semantic system and disturbances in the grammatical system); these two language dimensions are supported by different brain areas (temporal and frontal) in the left hemisphere. Furthermore, these two aspects of the language are developed at different ages during child's language acquisition, and they probably appeared at different historical moments during human evolution. Mechanisms of learning are different for both language systems: whereas the lexical/semantic knowledge is based in a declarative memory, grammatical knowledge corresponds to a procedural type of memory. Recognizing these two language dimensions can be crucial in understanding language evolution and human cognition.

  19. The overlapping community structure of structural brain network in young healthy individuals.

    Directory of Open Access Journals (Sweden)

    Kai Wu

    2011-05-01

    Full Text Available Community structure is a universal and significant feature of many complex networks in biology, society, and economics. Community structure has also been revealed in human brain structural and functional networks in previous studies. However, communities overlap and share many edges and nodes. Uncovering the overlapping community structure of complex networks remains largely unknown in human brain networks. Here, using regional gray matter volume, we investigated the structural brain network among 90 brain regions (according to a predefined anatomical atlas in 462 young, healthy individuals. Overlapped nodes between communities were defined by assuming that nodes (brain regions can belong to more than one community. We demonstrated that 90 brain regions were organized into 5 overlapping communities associated with several well-known brain systems, such as the auditory/language, visuospatial, emotion, decision-making, social, control of action, memory/learning, and visual systems. The overlapped nodes were mostly involved in an inferior-posterior pattern and were primarily related to auditory and visual perception. The overlapped nodes were mainly attributed to brain regions with higher node degrees and nodal efficiency and played a pivotal role in the flow of information through the structural brain network. Our results revealed fuzzy boundaries between communities by identifying overlapped nodes and provided new insights into the understanding of the relationship between the structure and function of the human brain. This study provides the first report of the overlapping community structure of the structural network of the human brain.

  20. Evolving the Language-Ready Brain and the Social Mechanisms that Support Language

    Science.gov (United States)

    Arbib, Michael A.

    2009-01-01

    We first review the mirror-system hypothesis on the evolution of the language-ready brain, stressing the important role of imitation and protosign in providing the scaffolding for protospeech. We then assess the role of social interaction and non-specific knowledge of language in the emergence of new sign languages in deaf communities (focusing on…

  1. Report on Networking and Programming Languages 2017

    KAUST Repository

    Bjorner, Nikolaj

    2017-10-26

    The third workshop on Networking and Programming Lan-guages, NetPL 2017, was held in conjunction with SIG-COMM 2017. The workshop series attracts invited speakers from academia and industry and a selection of contributed abstracts for short presentations. NetPL brings together re-searchers from the networking community and researchers from the programming languages and verification communities. The workshop series is a timely forum for exciting trends, technological and scientific advances in the intersection of these communities. We describe some of the high-lights from the invited talks through the lens of three trends: Advances in network machine architectures, network programming abstractions, and network verification. NetPL included five invited speakers, four from academia, and one from industry. The program contained six contributed talks out of eight submitted for presentation. The workshop organizers reviewed the abstracts for quality and scope. A total of 42 registrations were received and the attendance occupied the lecture room to the brink. Slides and abstracts from all talks are available from the workshop home page.1 Videos of the presentations are available in the NetPL YouTube channel.2.

  2. Neuroimaging of stroke recovery from aphasia - Insights into plasticity of the human language network.

    Science.gov (United States)

    Hartwigsen, Gesa; Saur, Dorothee

    2017-11-23

    The role of left and right hemisphere brain regions in language recovery after stroke-induced aphasia remains controversial. Here, we summarize how neuroimaging studies increase the current understanding of functional interactions, reorganization and plasticity in the language network. We first discuss the temporal dynamics across the time course of language recovery, with a main focus on longitudinal studies from the acute to the chronic phase after stroke. These studies show that the functional contribution of perilesional and spared left hemisphere as well as contralesional right hemisphere regions to language recovery changes over time. The second section introduces critical variables and recent advances on early prediction of subsequent outcome. In the third section, we outline how multi-method approaches that combine neuroimaging techniques with non-invasive brain stimulation elucidate mechanisms of plasticity and reorganization in the language network. These approaches provide novel insights into general mechanisms of plasticity in the language network and might ultimately support recovery processes during speech and language therapy. Finally, the neurobiological correlates of therapy-induced plasticity are discussed. We argue that future studies should integrate individualized approaches that might vary the combination of language therapy with specific non-invasive brain stimulation protocols across the time course of recovery. The way forward will include the combination of such approaches with large data sets obtained from multicentre studies. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Body language in the brain: constructing meaning from expressive movement

    Directory of Open Access Journals (Sweden)

    Christine Marie Tipper

    2015-08-01

    Full Text Available This fMRI study investigated neural systems that interpret body language - the meaningful emotive expressions conveyed by body movement. Participants watched videos of performers engaged in modern dance or pantomime that conveyed specific themes such as hope, agony, lust, or exhaustion. We tested whether the meaning of an affectively laden performance was decoded in localized brain substrates as a distinct property of action separable from other superficial features, such as choreography, kinematics, performer, and low-level visual stimuli. A repetition suppression (RS procedure was used to identify brain regions that decoded the meaningful affective state of a performer, as evidenced by decreased activity when emotive themes were repeated in successive performances. Because the theme was the only feature repeated across video clips that were otherwise entirely different, the occurrence of RS identified brain substrates that differentially coded the specific meaning of expressive performances. RS was observed bilaterally, extending anteriorly along middle and superior temporal gyri into temporal pole, medially into insula, rostrally into inferior orbitofrontal cortex, and caudally into hippocampus and amygdala. Behavioral data on a separate task indicated that interpreting themes from modern dance was more difficult than interpreting pantomime; a result that was also reflected in the fMRI data. There was greater RS in left hemisphere, suggesting that the more abstract metaphors used to express themes in dance compared to pantomime posed a greater challenge to brain substrates directly involved in decoding those themes. We propose that the meaning-sensitive temporal-orbitofrontal regions observed here comprise a superordinate functional module of a known hierarchical action observation network, which is critical to the construction of meaning from expressive movement. The findings are discussed with respect to a predictive coding model of action

  4. Body language in the brain: constructing meaning from expressive movement.

    Science.gov (United States)

    Tipper, Christine M; Signorini, Giulia; Grafton, Scott T

    2015-01-01

    This fMRI study investigated neural systems that interpret body language-the meaningful emotive expressions conveyed by body movement. Participants watched videos of performers engaged in modern dance or pantomime that conveyed specific themes such as hope, agony, lust, or exhaustion. We tested whether the meaning of an affectively laden performance was decoded in localized brain substrates as a distinct property of action separable from other superficial features, such as choreography, kinematics, performer, and low-level visual stimuli. A repetition suppression (RS) procedure was used to identify brain regions that decoded the meaningful affective state of a performer, as evidenced by decreased activity when emotive themes were repeated in successive performances. Because the theme was the only feature repeated across video clips that were otherwise entirely different, the occurrence of RS identified brain substrates that differentially coded the specific meaning of expressive performances. RS was observed bilaterally, extending anteriorly along middle and superior temporal gyri into temporal pole, medially into insula, rostrally into inferior orbitofrontal cortex, and caudally into hippocampus and amygdala. Behavioral data on a separate task indicated that interpreting themes from modern dance was more difficult than interpreting pantomime; a result that was also reflected in the fMRI data. There was greater RS in left hemisphere, suggesting that the more abstract metaphors used to express themes in dance compared to pantomime posed a greater challenge to brain substrates directly involved in decoding those themes. We propose that the meaning-sensitive temporal-orbitofrontal regions observed here comprise a superordinate functional module of a known hierarchical action observation network (AON), which is critical to the construction of meaning from expressive movement. The findings are discussed with respect to a predictive coding model of action understanding.

  5. Creative Cognition and Brain Network Dynamics

    Science.gov (United States)

    Beaty, Roger E.; Benedek, Mathias; Silvia, Paul J.; Schacter, Daniel L.

    2015-01-01

    Creative thinking is central to the arts, sciences, and everyday life. How does the brain produce creative thought? A series of recently published papers has begun to provide insight into this question, reporting a strikingly similar pattern of brain activity and connectivity across a range of creative tasks and domains, from divergent thinking to poetry composition to musical improvisation. This research suggests that creative thought involves dynamic interactions of large-scale brain systems, with the most compelling finding being that the default and executive control networks, which can show an antagonistic relationship, actually cooperate during creative cognition and artistic performance. These findings have implications for understanding how brain networks interact to support complex cognitive processes, particularly those involving goal-directed, self-generated thought. PMID:26553223

  6. [The language area of the brain: a functional reassessment].

    Science.gov (United States)

    Ardila, Alfredo; Bernal, Byron; Rosselli, Monica

    2016-02-01

    During the late 19th and early 20th century, a 'brain language area' was proposed corresponding to the peri-Sylvian region of the left hemisphere as concluded by clinical observations. This point of view has continued up today. Departing from contemporary neuroimaging studies, to re-analyze the location and extension the brain language area with regard to the different Brodmann areas. Using the method known as metaanalytic connectivity modeling seven meta-analytic studies of fMRI activity during the performance of different language tasks are analyzed. It was observed that two major brain systems can be distinguished: lexical/semantic, related with the Wernicke's area, that includes a core Wernicke's area (recognition of words) and an extended Wernicke's area (word associations); and grammatical system (language production and grammar) corresponding to the Broca's complex in the frontal lobe, and extending subcortically It is proposed that the insula plays a coordinating role in interconnecting these two brain language systems. Contemporary neuroimaging studies suggest that the brain language are is notoriously more extended than it was assumed one century ago based on clinical observations. As it was assumed during the 19th century, the insula seemingly plays a critical role in language.

  7. Neuronal and network computation in the brain

    International Nuclear Information System (INIS)

    Babloyantz, A.

    1999-01-01

    The concepts and methods of non-linear dynamics have been a powerful tool for studying some gamow aspects of brain dynamics. In this paper we show how, from time series analysis of electroencepholograms in sick and healthy subjects, chaotic nature of brain activity could be unveiled. This finding gave rise to the concept of spatiotemporal cortical chaotic networks which in turn was the foundation for a simple brain-like device which is able to become attentive, perform pattern recognition and motion detection. A new method of time series analysis is also proposed which demonstrates for the first time the existence of neuronal code in interspike intervals of coclear cells

  8. Resting network plasticity following brain injury.

    Directory of Open Access Journals (Sweden)

    Toru Nakamura

    Full Text Available The purpose of this study was to examine neural network properties at separate time-points during recovery from traumatic brain injury (TBI using graph theory. Whole-brain analyses of the topological properties of the fMRI signal were conducted in 6 participants at 3 months and 6 months following severe TBI. Results revealed alterations of network properties including a change in the degree distribution, reduced overall strength in connectivity, and increased "small-worldness" from 3 months to 6 months post injury. The findings here indicate that, during recovery from injury, the strength but not the number of network connections diminishes, so that over the course of recovery, the network begins to approximate what is observed in healthy adults. These are the first data examining functional connectivity in a disrupted neural system during recovery.

  9. Sign Language Recognition using Neural Networks

    Directory of Open Access Journals (Sweden)

    Sabaheta Djogic

    2014-11-01

    Full Text Available – Sign language plays a great role as communication media for people with hearing difficulties.In developed countries, systems are made for overcoming a problem in communication with deaf people. This encouraged us to develop a system for the Bosnian sign language since there is a need for such system. The work is done with the use of digital image processing methods providing a system that teaches a multilayer neural network using a back propagation algorithm. Images are processed by feature extraction methods, and by masking method the data set has been created. Training is done using cross validation method for better performance thus; an accuracy of 84% is achieved.

  10. Stress Impact on Resting State Brain Networks.

    Science.gov (United States)

    Soares, José Miguel; Sampaio, Adriana; Ferreira, Luís Miguel; Santos, Nadine Correia; Marques, Paulo; Marques, Fernanda; Palha, Joana Almeida; Cerqueira, João José; Sousa, Nuno

    2013-01-01

    Resting state brain networks (RSNs) are spatially distributed large-scale networks, evidenced by resting state functional magnetic resonance imaging (fMRI) studies. Importantly, RSNs are implicated in several relevant brain functions and present abnormal functional patterns in many neuropsychiatric disorders, for which stress exposure is an established risk factor. Yet, so far, little is known about the effect of stress in the architecture of RSNs, both in resting state conditions or during shift to task performance. Herein we assessed the architecture of the RSNs using functional magnetic resonance imaging (fMRI) in a cohort of participants exposed to prolonged stress (participants that had just finished their long period of preparation for the medical residence selection exam), and respective gender- and age-matched controls (medical students under normal academic activities). Analysis focused on the pattern of activity in resting state conditions and after deactivation. A volumetric estimation of the RSNs was also performed. Data shows that stressed participants displayed greater activation of the default mode (DMN), dorsal attention (DAN), ventral attention (VAN), sensorimotor (SMN), and primary visual (VN) networks than controls. Importantly, stressed participants also evidenced impairments in the deactivation of resting state-networks when compared to controls. These functional changes are paralleled by a constriction of the DMN that is in line with the pattern of brain atrophy observed after stress exposure. These results reveal that stress impacts on activation-deactivation pattern of RSNs, a finding that may underlie stress-induced changes in several dimensions of brain activity.

  11. Changes in cognitive state alter human functional brain networks

    Directory of Open Access Journals (Sweden)

    Malaak Nasser Moussa

    2011-08-01

    Full Text Available The study of the brain as a whole system can be accomplished using network theory principles. Research has shown that human functional brain networks during a resting state exhibit small-world properties and high degree nodes, or hubs, localized to brain areas consistent with the default mode network (DMN. However, the study of brain networks across different tasks and or cognitive states has been inconclusive. Research in this field is important because the underpinnings of behavioral output are inherently dependent on whether or not brain networks are dynamic. This is the first comprehensive study to evaluate multiple network metrics at a voxel-wise resolution in the human brain at both the whole brain and regional level under various conditions: resting state, visual stimulation, and multisensory (auditory and visual stimulation. Our results show that despite global network stability, functional brain networks exhibit considerable task-induced changes in connectivity, efficiency, and community structure at the regional level.

  12. Effect of second language exposure on brain activity for language processing among preschoolers.

    Science.gov (United States)

    Hidaka, Souta; Shibata, Hiroshi; Kurihara, Michiyo; Tanaka, Akihiro; Konno, Akitsugu; Maruyama, Suguru; Gyoba, Jiro; Hagiwara, Hiroko; Koizumi, Masatoshi

    2012-05-01

    We investigated brain activity in 3-5-year-old preschoolers as they listened to connected speech stimuli in Japanese (first language), English (second language), and Chinese (a rarely exposed, foreign language) using near-infrared spectroscopy. Unlike the younger preschoolers who had been exposed to English for almost 1 year, brain activity in the bilateral frontal regions of the older preschoolers who had been exposed to English for almost 2 years was higher for Japanese and English speech stimuli than for Chinese. This tendency seemed to be similar to that observed in adults who had learned English for some years. These results indicate that exposure to a second language affects brain activity to language stimuli among preschoolers. Copyright © 2012 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

  13. Presurgical Mapping of the Language Network Using Resting State Functional Connectivity

    OpenAIRE

    Tanaka, Naoaki; Stufflebeam, Steven M.

    2016-01-01

    Resting-state functional magnetic resonance imaging (Resting-state fMRI) is a tool for investigating the functional networks that arise during the resting-state of the brain. Recent advances of the resting-state fMRI analysis suggest its feasibility for evaluating language function. The most common clinical application is for presurgical mapping of cortex for a brain tumor or for resective epilespy surgery. In this article, we review the techniques and presurgical applications of resting-stat...

  14. Growth of language-related brain areas after foreign language learning.

    Science.gov (United States)

    Mårtensson, Johan; Eriksson, Johan; Bodammer, Nils Christian; Lindgren, Magnus; Johansson, Mikael; Nyberg, Lars; Lövdén, Martin

    2012-10-15

    The influence of adult foreign-language acquisition on human brain organization is poorly understood. We studied cortical thickness and hippocampal volumes of conscript interpreters before and after three months of intense language studies. Results revealed increases in hippocampus volume and in cortical thickness of the left middle frontal gyrus, inferior frontal gyrus, and superior temporal gyrus for interpreters relative to controls. The right hippocampus and the left superior temporal gyrus were structurally more malleable in interpreters acquiring higher proficiency in the foreign language. Interpreters struggling relatively more to master the language displayed larger gray matter increases in the middle frontal gyrus. These findings confirm structural changes in brain regions known to serve language functions during foreign-language acquisition. Copyright © 2012 Elsevier Inc. All rights reserved.

  15. Evolutionary Perspectives on Language and Brain Plasticity.

    Science.gov (United States)

    Deacon, Terrence W.

    2000-01-01

    This review discusses how general principles of brain development have contributed to both human brain plasticity and the acquisition of the human capacity for speech. Specifically, the role played by plastic developmental processes in the evolution and development of articulate control over vocalization in speech is examined. (Contains…

  16. Hubs in the human fetal brain network.

    Science.gov (United States)

    van den Heuvel, Marion I; Turk, Elise; Manning, Janessa H; Hect, Jasmine; Hernandez-Andrade, Edgar; Hassan, Sonia S; Romero, Roberto; van den Heuvel, Martijn P; Thomason, Moriah E

    2018-02-06

    Advances in neuroimaging and network analyses have lead to discovery of highly connected regions, or hubs, in the connectional architecture of the human brain. Whether these hubs emerge in utero, has yet to be examined. The current study addresses this question and aims to determine the location of neural hubs in human fetuses. Fetal resting-state fMRI data (N = 105) was used to construct connectivity matrices for 197 discrete brain regions. We discovered that within the connectional functional organization of the human fetal brain key hubs are emerging. Consistent with prior reports in infants, visual and motor regions were identified as emerging hub areas, specifically in cerebellar areas. We also found evidence for network hubs in association cortex, including areas remarkably close to the adult fusiform facial and Wernicke areas. Functional significance of hub structure was confirmed by computationally deleting hub versus random nodes and observing that global efficiency decreased significantly more when hubs were removed (p hubs may be important for facilitating network communication, they may also form potential points of vulnerability in fetal brain development. Copyright © 2018. Published by Elsevier Ltd.

  17. The development of brain network architecture.

    Science.gov (United States)

    Wierenga, Lara M; van den Heuvel, Martijn P; van Dijk, Sarai; Rijks, Yvonne; de Reus, Marcel A; Durston, Sarah

    2016-02-01

    Brain connectivity shows protracted development throughout childhood and adolescence, and, as such, the topology of brain networks changes during this period. The complexity of these changes with development is reflected by regional differences in maturation. This study explored age-related changes in network topology and regional developmental patterns during childhood and adolescence. We acquired two sets of Diffusion Weighted Imaging-scans and anatomical T1-weighted scans. The first dataset included 85 typically developing individuals (53 males; 32 females), aged between 7 and 23 years and was acquired on a Philips Achieva 1.5 Tesla scanner. A second dataset (N = 38) was acquired on a different (but identical) 1.5 T scanner and was used for independent replication of our results. We reconstructed whole brain networks using tractography. We operationalized fiber tract development as changes in mean diffusivity and radial diffusivity with age. Most fibers showed maturational changes in mean and radial diffusivity values throughout childhood and adolescence, likely reflecting increasing white matter integrity. The largest age-related changes were observed in association fibers within and between the frontal and parietal lobes. Furthermore, there was a simultaneous age-related decrease in average path length (P Brain Mapp 37:717-729, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  18. Brain metabolite levels and language abilities in preschool children.

    Science.gov (United States)

    Lebel, Catherine; MacMaster, Frank P; Dewey, Deborah

    2016-10-01

    Language acquisition occurs rapidly during early childhood and lays the foundation for future reading success. However, little is known about the brain-language relationships in young children. The goal of this study was to investigate relationships between brain metabolites and prereading language abilities in healthy preschool-aged children. Participants were 67 healthy children aged 3.0-5.4 years scanned on a 3T GE MR750w MRI scanner using short echo proton spectroscopy with a voxel placed in the anterior cingulate gyrus ( n  = 56) and/or near the left angular gyrus ( n  = 45). Children completed the NEPSY-II Phonological Processing and Speeded Naming subtests at the same time as their MRI scan. We calculated glutamate, glutamine, creatine/phosphocreatine, choline, inositol, and NAA concentrations, and correlated these with language skills. In the anterior cingulate, Phonological Processing Scaled Scores were significantly correlated with glutamate, creatine, and inositol concentrations. In the left angular gyrus, Speeded Naming Combined Scaled Scores showed trend correlations with choline and glutamine concentrations. For the first time, we demonstrate relationships between brain metabolites and prereading language abilities in young children. Our results show relationships between language and inositol and glutamate that may reflect glial differences underlying language function, and a relationship of language with creatine. The trend between Speeded Naming and choline is consistent with previous research in older children and adults; however, larger sample sizes are needed to confirm whether this relationship is indeed significant in young children. These findings help understand the brain basis of language, and may ultimately lead to earlier and more effective interventions for reading disabilities.

  19. Functional brain networks in schizophrenia: a review

    Directory of Open Access Journals (Sweden)

    Vince D Calhoun

    2009-08-01

    Full Text Available Functional magnetic resonance imaging (fMRI has become a major technique for studying cognitive function and its disruption in mental illness, including schizophrenia. The major proportion of imaging studies focused primarily upon identifying regions which hemodynamic response amplitudes covary with particular stimuli and differentiate between patient and control groups. In addition to such amplitude based comparisons, one can estimate temporal correlations and compute maps of functional connectivity between regions which include the variance associated with event related responses as well as intrinsic fluctuations of hemodynamic activity. Functional connectivity maps can be computed by correlating all voxels with a seed region when a spatial prior is available. An alternative are multivariate decompositions such as independent component analysis (ICA which extract multiple components, each of which is a spatially distinct map of voxels with a common time course. Recent work has shown that these networks are pervasive in relaxed resting and during task performance and hence provide robust measures of intact and disturbed brain activity. This in turn bears the prospect of yielding biomarkers for schizophrenia, which can be described both in terms of disrupted local processing as well as altered global connectivity between large scale networks. In this review we will summarize functional connectivity measures with a focus upon work with ICA and discuss the meaning of intrinsic fluctuations. In addition, examples of how brain networks have been used for classification of disease will be shown. We present work with functional network connectivity, an approach that enables the evaluation of the interplay between multiple networks and how they are affected in disease. We conclude by discussing new variants of ICA for extracting maximally group discriminative networks from data. In summary, it is clear that identification of brain networks and their

  20. Hierarchical modularity in human brain functional networks

    Directory of Open Access Journals (Sweden)

    David Meunier

    2009-10-01

    Full Text Available The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules” decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

  1. Network effects of deep brain stimulation.

    Science.gov (United States)

    Alhourani, Ahmad; McDowell, Michael M; Randazzo, Michael J; Wozny, Thomas A; Kondylis, Efstathios D; Lipski, Witold J; Beck, Sarah; Karp, Jordan F; Ghuman, Avniel S; Richardson, R Mark

    2015-10-01

    The ability to differentially alter specific brain functions via deep brain stimulation (DBS) represents a monumental advance in clinical neuroscience, as well as within medicine as a whole. Despite the efficacy of DBS in the treatment of movement disorders, for which it is often the gold-standard therapy when medical management becomes inadequate, the mechanisms through which DBS in various brain targets produces therapeutic effects is still not well understood. This limited knowledge is a barrier to improving efficacy and reducing side effects in clinical brain stimulation. A field of study related to assessing the network effects of DBS is gradually emerging that promises to reveal aspects of the underlying pathophysiology of various brain disorders and their response to DBS that will be critical to advancing the field. This review summarizes the nascent literature related to network effects of DBS measured by cerebral blood flow and metabolic imaging, functional imaging, and electrophysiology (scalp and intracranial electroencephalography and magnetoencephalography) in order to establish a framework for future studies. Copyright © 2015 the American Physiological Society.

  2. Network effects of deep brain stimulation

    Science.gov (United States)

    Alhourani, Ahmad; McDowell, Michael M.; Randazzo, Michael J.; Wozny, Thomas A.; Kondylis, Efstathios D.; Lipski, Witold J.; Beck, Sarah; Karp, Jordan F.; Ghuman, Avniel S.

    2015-01-01

    The ability to differentially alter specific brain functions via deep brain stimulation (DBS) represents a monumental advance in clinical neuroscience, as well as within medicine as a whole. Despite the efficacy of DBS in the treatment of movement disorders, for which it is often the gold-standard therapy when medical management becomes inadequate, the mechanisms through which DBS in various brain targets produces therapeutic effects is still not well understood. This limited knowledge is a barrier to improving efficacy and reducing side effects in clinical brain stimulation. A field of study related to assessing the network effects of DBS is gradually emerging that promises to reveal aspects of the underlying pathophysiology of various brain disorders and their response to DBS that will be critical to advancing the field. This review summarizes the nascent literature related to network effects of DBS measured by cerebral blood flow and metabolic imaging, functional imaging, and electrophysiology (scalp and intracranial electroencephalography and magnetoencephalography) in order to establish a framework for future studies. PMID:26269552

  3. Brain networks for integrative rhythm formation.

    Directory of Open Access Journals (Sweden)

    Michael H Thaut

    2008-05-01

    Full Text Available Performance of externally paced rhythmic movements requires brain and behavioral integration of sensory stimuli with motor commands. The underlying brain mechanisms to elaborate beat-synchronized rhythm and polyrhythms that musicians readily perform may differ. Given known roles in perceiving time and repetitive movements, we hypothesized that basal ganglia and cerebellar structures would have greater activation for polyrhythms than for on-the-beat rhythms.Using functional MRI methods, we investigated brain networks for performing rhythmic movements paced by auditory cues. Musically trained participants performed rhythmic movements at 2 and 3 Hz either at a 1:1 on-the-beat or with a 3:2 or a 2:3 stimulus-movement structure. Due to their prior musical experience, participants performed the 3:2 or 2:3 rhythmic movements automatically. Both the isorhythmic 1:1 and the polyrhythmic 3:2 or 2:3 movements yielded the expected activation in contralateral primary motor cortex and related motor areas and ipsilateral cerebellum. Direct comparison of functional MRI signals obtained during 3:2 or 2:3 and on-the-beat rhythms indicated activation differences bilaterally in the supplementary motor area, ipsilaterally in the supramarginal gyrus and caudate-putamen and contralaterally in the cerebellum.The activated brain areas suggest the existence of an interconnected brain network specific for complex sensory-motor rhythmic integration that might have specificity for elaboration of musical abilities.

  4. Brain signatures of artificial language processing: Evidence challenging the critical period hypothesis

    OpenAIRE

    Friederici, Angela D.; Steinhauer, Karsten; Pfeifer, Erdmut

    2002-01-01

    Adult second language learning seems to be more difficult and less efficient than first language acquisition during childhood. By using event-related brain potentials, we show that adults who learned a miniature artificial language display a similar real-time pattern of brain activation when processing this language as native speakers do when processing natural languages. Participants trained in the artificial language showed two event-related brain potential compo...

  5. Intrinsic Functional Connectivity in the Adult Brain and Success in Second-Language Learning.

    Science.gov (United States)

    Chai, Xiaoqian J; Berken, Jonathan A; Barbeau, Elise B; Soles, Jennika; Callahan, Megan; Chen, Jen-Kai; Klein, Denise

    2016-01-20

    There is considerable variability in an individual's ability to acquire a second language (L2) during adulthood. Using resting-state fMRI data acquired before training in English speakers who underwent a 12 week intensive French immersion training course, we investigated whether individual differences in intrinsic resting-state functional connectivity relate to a person's ability to acquire an L2. We focused on two key aspects of language processing--lexical retrieval in spontaneous speech and reading speed--and computed whole-brain functional connectivity from two regions of interest in the language network, namely the left anterior insula/frontal operculum (AI/FO) and the visual word form area (VWFA). Connectivity between the left AI/FO and left posterior superior temporal gyrus (STG) and between the left AI/FO and dorsal anterior cingulate cortex correlated positively with improvement in L2 lexical retrieval in spontaneous speech. Connectivity between the VWFA and left mid-STG correlated positively with improvement in L2 reading speed. These findings are consistent with the different language functions subserved by subcomponents of the language network and suggest that the human capacity to learn an L2 can be predicted by an individual's intrinsic functional connectivity within the language network. Significance statement: There is considerable variability in second-language learning abilities during adulthood. We investigated whether individual differences in intrinsic functional connectivity in the adult brain relate to success in second-language learning, using resting-state functional magnetic resonance imaging in English speakers who underwent a 12 week intensive French immersion training course. We found that pretraining functional connectivity within two different language subnetworks correlated strongly with learning outcome in two different language skills: lexical retrieval in spontaneous speech and reading speed. Our results suggest that the human

  6. The Structural Connectivity Underpinning Language Aptitude, Working Memory, and IQ in the Perisylvian Language Network

    NARCIS (Netherlands)

    Xiang, H.; Dediu, D.; Roberts, M.J.; Oort, E.S.B. van; Norris, D.; Hagoort, P.

    2012-01-01

    In this article, we report the results of a study on the relationship between individual differences in language learning aptitude and the structural connectivity of language pathways in the adult brain, the first of its kind. We measured four components of language aptitude (vocabulary learning;

  7. The Structural Connectivity Underpinning Language Aptitude, Working Memory, and IQ in the Perisylvian Language Network

    Science.gov (United States)

    Xiang, Huadong; Dediu, Dan; Roberts, Leah; van Oort, Erik; Norris, David G.; Hagoort, Peter

    2012-01-01

    In this article, we report the results of a study on the relationship between individual differences in language learning aptitude and the structural connectivity of language pathways in the adult brain, the first of its kind. We measured four components of language aptitude ("vocabulary learning"; "sound recognition"; "sound-symbol…

  8. Bayesian Joint Modeling of Multiple Brain Functional Networks

    OpenAIRE

    Lukemire, Joshua; Kundu, Suprateek; Pagnoni, Giuseppe; Guo, Ying

    2017-01-01

    Brain function is organized in coordinated modes of spatio-temporal activity (functional networks) exhibiting an intrinsic baseline structure with variations under different experimental conditions. Existing approaches for uncovering such network structures typically do not explicitly model shared and differential patterns across networks, thus potentially reducing the detection power. We develop an integrative modeling approach for jointly modeling multiple brain networks across experimental...

  9. Brain connectivity associated with cascading levels of language

    Science.gov (United States)

    Richards, Todd; Nagy, William; Abbott, Robert; Berninger, Virginia

    2016-01-01

    Typical oral and written language learners (controls) (5 girls, 4 boys) completed fMRI reading judgment tasks (sub-word grapheme-phoneme, word spelling, sentences with and without spelling foils, affixed words, sentences with and without affix foils, and multi-sentence). Analyses identified connectivity within and across adjacent levels (units) of language in reading: from subword to word to syntax in Set I and from word to syntax to multi-sentence in Set II). Typicals were compared to (a) students with dyslexia (6 girls, 10 boys) on the subword and word tasks in Set I related to levels of language impaired in dyslexia, and (b) students with oral and written language learning disability (OWL LD) (3 girls, 2 boys) on the morphology and syntax tasks in Set II, related to levels of language impaired in OWL LD. Results for typical language learners showed that adjacent levels of language in the reading brain share common and unique connectivity. The dyslexia group showed over-connectivity to a greater degree on the imaging tasks related to their levels of language impairments than the OWL LD group who showed under-connectivity to a greater degree than did the dyslexia group on the imaging tasks related to their levels of language impairment. Results for these students in grades 4 to 9 (ages 9 to 14) are discussed in reference to the contribution of patterns of connectivity across levels of language to understanding the nature of persisting dyslexia and dysgraphia despite early intervention. PMID:28127444

  10. Presurgical Mapping of the Language Network Using Resting-state Functional Connectivity.

    Science.gov (United States)

    Tanaka, Naoaki; Stufflebeam, Steven M

    2016-02-01

    Resting-state functional magnetic resonance imaging (resting-state fMRI) is a tool for investigating the functional networks that arise during the resting state of the brain. Recent advances of the resting-state fMRI analysis suggest its feasibility for evaluating language function. The most common clinical application is for presurgical mapping of cortex for a brain tumor or for resective epilespy surgery. In this article, we review the techniques and presurgical applications of resting-state fMRI analysis for language evaluation, and discuss the use in the clinical setting, focusing on planning for neurosurgery.

  11. Presurgical Mapping of the Language Network Using Resting State Functional Connectivity

    Science.gov (United States)

    Tanaka, Naoaki; Stufflebeam, Steven M.

    2016-01-01

    Resting-state functional magnetic resonance imaging (Resting-state fMRI) is a tool for investigating the functional networks that arise during the resting-state of the brain. Recent advances of the resting-state fMRI analysis suggest its feasibility for evaluating language function. The most common clinical application is for presurgical mapping of cortex for a brain tumor or for resective epilespy surgery. In this article, we review the techniques and presurgical applications of resting-state fMRI analysis for language evaluation, and discuss the use in the clinical setting, focusing on planning for neurosurgery. PMID:26848557

  12. Testosterone affects language areas of the adult human brain.

    Science.gov (United States)

    Hahn, Andreas; Kranz, Georg S; Sladky, Ronald; Kaufmann, Ulrike; Ganger, Sebastian; Hummer, Allan; Seiger, Rene; Spies, Marie; Vanicek, Thomas; Winkler, Dietmar; Kasper, Siegfried; Windischberger, Christian; Swaab, Dick F; Lanzenberger, Rupert

    2016-05-01

    Although the sex steroid hormone testosterone is integrally involved in the development of language processing, ethical considerations mostly limit investigations to single hormone administrations. To circumvent this issue we assessed the influence of continuous high-dose hormone application in adult female-to-male transsexuals. Subjects underwent magnetic resonance imaging before and after 4 weeks of testosterone treatment, with each scan including structural, diffusion weighted and functional imaging. Voxel-based morphometry analysis showed decreased gray matter volume with increasing levels of bioavailable testosterone exclusively in Broca's and Wernicke's areas. Particularly, this may link known sex differences in language performance to the influence of testosterone on relevant brain regions. Using probabilistic tractography, we further observed that longitudinal changes in testosterone negatively predicted changes in mean diffusivity of the corresponding structural connection passing through the extreme capsule. Considering a related increase in myelin staining in rodents, this potentially reflects a strengthening of the fiber tract particularly involved in language comprehension. Finally, functional images at resting-state were evaluated, showing increased functional connectivity between the two brain regions with increasing testosterone levels. These findings suggest testosterone-dependent neuroplastic adaptations in adulthood within language-specific brain regions and connections. Importantly, deteriorations in gray matter volume seem to be compensated by enhancement of corresponding structural and functional connectivity. Hum Brain Mapp 37:1738-1748, 2016. © 2016 Wiley Periodicals, Inc. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  13. Identifying modular relations in complex brain networks

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther; Mørup, Morten; Siebner, Hartwig

    2012-01-01

    and obtains comparable reproducibility and predictability. For resting state functional magnetic resonance imaging data from 30 healthy controls the IRM model is also superior to the two simpler alternatives, suggesting that brain networks indeed exhibit universal complex relational structure......We evaluate the infinite relational model (IRM) against two simpler alternative nonparametric Bayesian models for identifying structures in multi subject brain networks. The models are evaluated for their ability to predict new data and infer reproducible structures. Prediction and reproducibility...... are measured within the data driven NPAIRS split-half framework. Using synthetic data drawn from each of the generative models we show that the IRM model outperforms the two competing models when data contain relational structure. For data drawn from the other two simpler models the IRM does not overfit...

  14. Mutated Genes in Schizophrenia Map to Brain Networks

    Science.gov (United States)

    ... Matters NIH Research Matters August 12, 2013 Mutated Genes in Schizophrenia Map to Brain Networks Schizophrenia networks ... have a high number of spontaneous mutations in genes that form a network in the front region ...

  15. Stress Impact on Resting State Brain Networks.

    Directory of Open Access Journals (Sweden)

    José Miguel Soares

    Full Text Available Resting state brain networks (RSNs are spatially distributed large-scale networks, evidenced by resting state functional magnetic resonance imaging (fMRI studies. Importantly, RSNs are implicated in several relevant brain functions and present abnormal functional patterns in many neuropsychiatric disorders, for which stress exposure is an established risk factor. Yet, so far, little is known about the effect of stress in the architecture of RSNs, both in resting state conditions or during shift to task performance. Herein we assessed the architecture of the RSNs using functional magnetic resonance imaging (fMRI in a cohort of participants exposed to prolonged stress (participants that had just finished their long period of preparation for the medical residence selection exam, and respective gender- and age-matched controls (medical students under normal academic activities. Analysis focused on the pattern of activity in resting state conditions and after deactivation. A volumetric estimation of the RSNs was also performed. Data shows that stressed participants displayed greater activation of the default mode (DMN, dorsal attention (DAN, ventral attention (VAN, sensorimotor (SMN, and primary visual (VN networks than controls. Importantly, stressed participants also evidenced impairments in the deactivation of resting state-networks when compared to controls. These functional changes are paralleled by a constriction of the DMN that is in line with the pattern of brain atrophy observed after stress exposure. These results reveal that stress impacts on activation-deactivation pattern of RSNs, a finding that may underlie stress-induced changes in several dimensions of brain activity.

  16. The Influence of Japanese Anime Language to Chinese Network Buzzwords

    OpenAIRE

    Cai Jin Chang

    2016-01-01

    In this paper, the influence of Japanese anime language to Chinese network buzzwords was studied, and the maturity and rigor were quoted. The Japanese anime language refined, creative can be so popular in the factors of psychologies also was analyzed. According to these studies, some suggestions were put forward that how to standardize the network buzzwords and how to raise its taste.

  17. Connections for auditory language in the human brain.

    Science.gov (United States)

    Gierhan, Sarah M E

    2013-11-01

    The white matter bundles that underlie comprehension and production of language have been investigated for a number of years. Several studies have examined which fiber bundles (or tracts) are involved in auditory language processing, and which kind of language information is transmitted by which fiber tract. However, there is much debate about exactly which fiber tracts are involved, their precise course in the brain, how they should be named, and which functions they fulfill. Therefore, the present article reviews the available language-related literature, and educes a neurocognitive model of the pathways for auditory language processing. Besides providing an overview of the current methods used for relating fiber anatomy to function, this article details the precise anatomy of the fiber tracts and their roles in phonological, semantic and syntactic processing, articulation, and repetition. Copyright © 2012 Elsevier Inc. All rights reserved.

  18. Natural Language Video Description using Deep Recurrent Neural Networks

    Science.gov (United States)

    2015-11-23

    language with a single deep neural network. We use deep recurrent nets (RNNs), which have recently demonstrated strong results for machine translation (MT...Donahue, Marcus Rohrbach, Raymond Mooney, and Kate Saenko. Translating videos to natural language using deep recurrent neural net - works. In NAACL, 2015...Natural Language Video Description using Deep Recurrent Neural Networks Subhashini Venugopalan University of Texas at Austin vsub@cs.utexas.edu

  19. Functional language shift to the right hemisphere in patients with language-eloquent brain tumors.

    Science.gov (United States)

    Krieg, Sandro M; Sollmann, Nico; Hauck, Theresa; Ille, Sebastian; Foerschler, Annette; Meyer, Bernhard; Ringel, Florian

    2013-01-01

    Language function is mainly located within the left hemisphere of the brain, especially in right-handed subjects. However, functional MRI (fMRI) has demonstrated changes of language organization in patients with left-sided perisylvian lesions to the right hemisphere. Because intracerebral lesions can impair fMRI, this study was designed to investigate human language plasticity with a virtual lesion model using repetitive navigated transcranial magnetic stimulation (rTMS). Fifteen patients with lesions of left-sided language-eloquent brain areas and 50 healthy and purely right-handed participants underwent bilateral rTMS language mapping via an object-naming task. All patients were proven to have left-sided language function during awake surgery. The rTMS-induced language errors were categorized into 6 different error types. The error ratio (induced errors/number of stimulations) was determined for each brain region on both hemispheres. A hemispheric dominance ratio was then defined for each region as the quotient of the error ratio (left/right) of the corresponding area of both hemispheres (ratio >1 = left dominant; ratio language-eloquent lesions showed a statistically significantly lower ratio than healthy participants concerning "all errors" and "all errors without hesitations", which indicates a higher participation of the right hemisphere in language function. Yet, there was no cortical region with pronounced difference in language dominance compared to the whole hemisphere. This is the first study that shows by means of an anatomically accurate virtual lesion model that a shift of language function to the non-dominant hemisphere can occur.

  20. Consciousness, cognition and brain networks: New perspectives.

    Science.gov (United States)

    Aldana, E M; Valverde, J L; Fábregas, N

    2016-10-01

    A detailed analysis of the literature on consciousness and cognition mechanisms based on the neural networks theory is presented. The immune and inflammatory response to the anesthetic-surgical procedure induces modulation of neuronal plasticity by influencing higher cognitive functions. Anesthetic drugs can cause unconsciousness, producing a functional disruption of cortical and thalamic cortical integration complex. The external and internal perceptions are processed through an intricate network of neural connections, involving the higher nervous activity centers, especially the cerebral cortex. This requires an integrated model, formed by neural networks and their interactions with highly specialized regions, through large-scale networks, which are distributed throughout the brain collecting information flow of these perceptions. Functional and effective connectivity between large-scale networks, are essential for consciousness, unconsciousness and cognition. It is what is called the "human connectome" or map neural networks. Copyright © 2014 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

  1. Functional brain networks involved in reality monitoring.

    Science.gov (United States)

    Metzak, Paul D; Lavigne, Katie M; Woodward, Todd S

    2015-08-01

    Source monitoring refers to the recollection of variables that specify the context and conditions in which a memory episode was encoded. This process involves using the qualitative and quantitative features of a memory trace to distinguish its source. One specific class of source monitoring is reality monitoring, which involves distinguishing internally generated from externally generated information, that is, memories of imagined events from real events. The purpose of the present study was to identify functional brain networks that underlie reality monitoring, using an alternative type of source monitoring as a control condition. On the basis of previous studies on self-referential thinking, it was expected that a medial prefrontal cortex (mPFC) based network would be more active during reality monitoring than the control condition, due to the requirement to focus on a comparison of internal (self) and external (other) source information. Two functional brain networks emerged from this analysis, one reflecting increasing task-related activity, and one reflecting decreasing task-related activity. The second network was mPFC based, and was characterized by task-related deactivations in areas resembling the default-mode network; namely, the mPFC, middle temporal gyri, lateral parietal regions, and the precuneus, and these deactivations were diminished during reality monitoring relative to source monitoring, resulting in higher activity during reality monitoring. This result supports previous research suggesting that self-referential thinking involves the mPFC, but extends this to a network-level interpretation of reality monitoring. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. The Virtual Brain: a simulator of primate brain network dynamics.

    Science.gov (United States)

    Sanz Leon, Paula; Knock, Stuart A; Woodman, M Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

    2013-01-01

    We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications.

  3. English Language Education On-Line Game and Brain Connectivity

    Science.gov (United States)

    Hong, Ji Sun; Han, Doug Hyun; Kim, Young In; Bae, Su Jin

    2017-01-01

    The HoDoo English game was developed to take advantage of the benefits attributed to on-line games while teaching English to native Korean speakers. We expected to see that the improvements in the subjects' English language abilities after playing the HoDoo English game would be associated with increased brain functional connectivity in the areas…

  4. Identifying large-scale brain networks in fragile X syndrome.

    Science.gov (United States)

    Hall, Scott S; Jiang, Heidi; Reiss, Allan L; Greicius, Michael D

    2013-11-01

    Fragile X syndrome (FXS) is an X-linked neurogenetic disorder characterized by a cognitive and behavioral phenotype resembling features of autism spectrum disorder. Until now, research has focused largely on identifying regional differences in brain structure and function between individuals with FXS and various control groups. Very little is known about the large-scale brain networks that may underlie the cognitive and behavioral symptoms of FXS. To identify large-scale, resting-state networks in FXS that differ from control individuals matched on age, IQ, and severity of behavioral and cognitive symptoms. Cross-sectional, in vivo neuroimaging study conducted in an academic medical center. Participants (aged 10-23 years) included 17 males and females with FXS and 16 males and females serving as controls. Univariate voxel-based morphometric analyses, fractional amplitude of low-frequency fluctuations (fALFF) analysis, and group-independent component analysis with dual regression. Patients with FXS showed decreased functional connectivity in the salience, precuneus, left executive control, language, and visuospatial networks compared with controls. Decreased fALFF in the bilateral insular, precuneus, and anterior cingulate cortices also was found in patients with FXS compared with control participants. Furthermore, fALFF in the left insular cortex was significantly positively correlated with IQ in patients with FXS. Decreased gray matter density, resting-state connectivity, and fALFF converged in the left insular cortex in patients with FXS. Fragile X syndrome results in widespread reductions in functional connectivity across multiple cognitive and affective brain networks. Converging structural and functional abnormalities in the left insular cortex, a region also implicated in individuals diagnosed with autism spectrum disorder, suggests that insula integrity and connectivity may be compromised in FXS. This method could prove useful in establishing an imaging

  5. Exploring Mechanisms Underlying Impaired Brain Function in Gulf War Illness through Advanced Network Analysis

    Science.gov (United States)

    2017-10-01

    networks of the brain responsible for visual processing, mood regulation, motor coordination, sensory processing, and language command, but increased...GWI Syndromes 1, 2, and 3; neurologic symptoms, neurocognitive; affective; pain; sensory ; resting state functional MRI; independent components analysis...neuropathic pain, memory and concentration deficits, vestibular disturbances, and depression. The objective/goal of this project titled, “Exploring

  6. Bayesian Recurrent Neural Network for Language Modeling.

    Science.gov (United States)

    Chien, Jen-Tzung; Ku, Yuan-Chu

    2016-02-01

    A language model (LM) is calculated as the probability of a word sequence that provides the solution to word prediction for a variety of information systems. A recurrent neural network (RNN) is powerful to learn the large-span dynamics of a word sequence in the continuous space. However, the training of the RNN-LM is an ill-posed problem because of too many parameters from a large dictionary size and a high-dimensional hidden layer. This paper presents a Bayesian approach to regularize the RNN-LM and apply it for continuous speech recognition. We aim to penalize the too complicated RNN-LM by compensating for the uncertainty of the estimated model parameters, which is represented by a Gaussian prior. The objective function in a Bayesian classification network is formed as the regularized cross-entropy error function. The regularized model is constructed not only by calculating the regularized parameters according to the maximum a posteriori criterion but also by estimating the Gaussian hyperparameter by maximizing the marginal likelihood. A rapid approximation to a Hessian matrix is developed to implement the Bayesian RNN-LM (BRNN-LM) by selecting a small set of salient outer-products. The proposed BRNN-LM achieves a sparser model than the RNN-LM. Experiments on different corpora show the robustness of system performance by applying the rapid BRNN-LM under different conditions.

  7. Broadband criticality of human brain network synchronization.

    Science.gov (United States)

    Kitzbichler, Manfred G; Smith, Marie L; Christensen, Søren R; Bullmore, Ed

    2009-03-01

    Self-organized criticality is an attractive model for human brain dynamics, but there has been little direct evidence for its existence in large-scale systems measured by neuroimaging. In general, critical systems are associated with fractal or power law scaling, long-range correlations in space and time, and rapid reconfiguration in response to external inputs. Here, we consider two measures of phase synchronization: the phase-lock interval, or duration of coupling between a pair of (neurophysiological) processes, and the lability of global synchronization of a (brain functional) network. Using computational simulations of two mechanistically distinct systems displaying complex dynamics, the Ising model and the Kuramoto model, we show that both synchronization metrics have power law probability distributions specifically when these systems are in a critical state. We then demonstrate power law scaling of both pairwise and global synchronization metrics in functional MRI and magnetoencephalographic data recorded from normal volunteers under resting conditions. These results strongly suggest that human brain functional systems exist in an endogenous state of dynamical criticality, characterized by a greater than random probability of both prolonged periods of phase-locking and occurrence of large rapid changes in the state of global synchronization, analogous to the neuronal "avalanches" previously described in cellular systems. Moreover, evidence for critical dynamics was identified consistently in neurophysiological systems operating at frequency intervals ranging from 0.05-0.11 to 62.5-125 Hz, confirming that criticality is a property of human brain functional network organization at all frequency intervals in the brain's physiological bandwidth.

  8. Disrupting the brain to validate hypotheses on the neurobiology of language

    Directory of Open Access Journals (Sweden)

    Liuba ePapeo

    2013-04-01

    Full Text Available Comprehension of words is an important part of the language faculty, involving the joint activity of frontal and temporo-parietal brain regions. Transcranial Magnetic Stimulation (TMS enables the controlled perturbation of brain activity, and thus offers a unique tool to test specific predictions about the causal relationship between brain regions and language understanding. This potential has been exploited to better define the role of regions that are classically accepted as part of the language-semantic network. For instance, TMS has contributed to establish the semantic relevance of the left anterior temporal lobe, or to solve the ambiguity between the semantic versus phonological function assigned to the left inferior frontal gyrus. We consider, more closely, the results from studies where the same technique, similar paradigms (lexical-semantic tasks and materials (words have been used to assess the relevance of regions outside the classically-defined language-semantic network – i.e., precentral motor regions – for the semantic analysis of words. This research shows that different aspects of the left precentral gyrus (primary motor and premotor sites are sensitive to the action-non action distinction of words’ meanings. However, the behavioral changes due to TMS over these sites are incongruent with what is expected after perturbation of a task-relevant brain region. Thus, the relationship between motor activity and language-semantic behavior remains far from clear. A better understanding of this issue could be guaranteed by investigating functional interactions between motor sites and semantically-relevant regions.

  9. The Union of Shortest Path Trees of Functional Brain Networks

    NARCIS (Netherlands)

    Meier, J.; Tewarie, P.; Van Mieghem, P.

    2015-01-01

    Communication between brain regions is still insufficiently understood. Applying concepts from network science has shown to be successful in gaining insight in the functioning of the brain. Recent work has implicated that especially shortest paths in the structural brain network seem to play a major

  10. Musicianship and Tone Language Experience Are Associated with Differential Changes in Brain Signal Variability.

    Science.gov (United States)

    Hutka, Stefanie; Carpentier, Sarah M; Bidelman, Gavin M; Moreno, Sylvain; McIntosh, Anthony R

    2016-12-01

    Musicianship has been associated with auditory processing benefits. It is unclear, however, whether pitch processing experience in nonmusical contexts, namely, speaking a tone language, has comparable associations with auditory processing. Studies comparing the auditory processing of musicians and tone language speakers have shown varying degrees of between-group similarity with regard to perceptual processing benefits and, particularly, nonlinguistic pitch processing. To test whether the auditory abilities honed by musicianship or speaking a tone language differentially impact the neural networks supporting nonlinguistic pitch processing (relative to timbral processing), we employed a novel application of brain signal variability (BSV) analysis. BSV is a metric of information processing capacity and holds great potential for understanding the neural underpinnings of experience-dependent plasticity. Here, we measured BSV in electroencephalograms of musicians, tone language-speaking nonmusicians, and English-speaking nonmusicians (controls) during passive listening of music and speech sound contrasts. Although musicians showed greater BSV across the board, each group showed a unique spatiotemporal distribution in neural network engagement: Controls had greater BSV for speech than music; tone language-speaking nonmusicians showed the opposite effect; musicians showed similar BSV for both domains. Collectively, results suggest that musical and tone language pitch experience differentially affect auditory processing capacity within the cerebral cortex. However, information processing capacity is graded: More experience with pitch is associated with greater BSV when processing this cue. Higher BSV in musicians may suggest increased information integration within the brain networks subserving speech and music, which may be related to their well-documented advantages on a wide variety of speech-related tasks.

  11. Interfaces, syntactic movement, and neural activation: A new perspective on the implementation of language in the brain

    DEFF Research Database (Denmark)

    Christensen, Ken Ramshøj

    2008-01-01

    Studies of language deficits as well as neuroimaging studies indicate that syntactic processing of displaced constituents is implemented in the brain as a distributed cortical network of modules. The data from the present fMRI study on two types of syntactic movement in Danish offers further...

  12. [Brain plasticity for language in children and adolescents].

    Science.gov (United States)

    Narbona, Juan; Crespo-Eguilaz, Nerea

    2012-02-29

    Plasticity makes possible adaptative modelling of the nervous system to experiences i.e. learning and development. To review current literature on clinical long term evolution and functional magnetic resonance imaging (fMRI) features of brain remodelling after focal stroke in left perisylvian regions involved in basic language processing during infancy and childhood. Each of the main neurocognitive subsystems develops with different timing, so altered plasticity and vulnerability are diverse, according with age at insult and its topography. Genetic programming makes human brain capable for installing basic formal linguistic abilities on an associative perisylvian subsystem, highly specialised. A focal lesion of this region leads to remodelling phenomena by disinhibition of contralateral frontal and perisylvian structures and by a more or less efficacious activation of neighboring homolateral cortex, as it has been shown by fMRI studies and DTI tractography. As a result, very early local stroke to language areas is generally well compensated in terms of linguistic behaviour. Meanwhile acquired aphasias into middle and late childhood, even if they have a better prognosis than in adults, they fail to resume without lexical access defaults and/or difficulties in written language. Brain plasticity can promote restoration and further development of language following a stroke in left peri-sylvian areas, specially when lesion occurs at perinatal to middle childhood.

  13. Brain. Conscious and Unconscious Mechanisms of Cognition, Emotions, and Language

    Directory of Open Access Journals (Sweden)

    Roman Ilin

    2012-12-01

    Full Text Available Conscious and unconscious brain mechanisms, including cognition, emotions and language are considered in this review. The fundamental mechanisms of cognition include interactions between bottom-up and top-down signals. The modeling of these interactions since the 1960s is briefly reviewed, analyzing the ubiquitous difficulty: incomputable combinatorial complexity (CC. Fundamental reasons for CC are related to the Gödel’s difficulties of logic, a most fundamental mathematical result of the 20th century. Many scientists still “believed” in logic because, as the review discusses, logic is related to consciousness; non-logical processes in the brain are unconscious. CC difficulty is overcome in the brain by processes “from vague-unconscious to crisp-conscious” (representations, plans, models, concepts. These processes are modeled by dynamic logic, evolving from vague and unconscious representations toward crisp and conscious thoughts. We discuss experimental proofs and relate dynamic logic to simulators of the perceptual symbol system. “From vague to crisp” explains interactions between cognition and language. Language is mostly conscious, whereas cognition is only rarely so; this clarifies much about the mind that might seem mysterious. All of the above involve emotions of a special kind, aesthetic emotions related to knowledge and to cognitive dissonances. Cognition-language-emotional mechanisms operate throughout the hierarchy of the mind and create all higher mental abilities. The review discusses cognitive functions of the beautiful, sublime, music.

  14. Brain. Conscious and unconscious mechanisms of cognition, emotions, and language.

    Science.gov (United States)

    Perlovsky, Leonid; Ilin, Roman

    2012-12-18

    Conscious and unconscious brain mechanisms, including cognition, emotions and language are considered in this review. The fundamental mechanisms of cognition include interactions between bottom-up and top-down signals. The modeling of these interactions since the 1960s is briefly reviewed, analyzing the ubiquitous difficulty: incomputable combinatorial complexity (CC). Fundamental reasons for CC are related to the Gödel's difficulties of logic, a most fundamental mathematical result of the 20th century. Many scientists still "believed" in logic because, as the review discusses, logic is related to consciousness; non-logical processes in the brain are unconscious. CC difficulty is overcome in the brain by processes "from vague-unconscious to crisp-conscious" (representations, plans, models, concepts). These processes are modeled by dynamic logic, evolving from vague and unconscious representations toward crisp and conscious thoughts. We discuss experimental proofs and relate dynamic logic to simulators of the perceptual symbol system. "From vague to crisp" explains interactions between cognition and language. Language is mostly conscious, whereas cognition is only rarely so; this clarifies much about the mind that might seem mysterious. All of the above involve emotions of a special kind, aesthetic emotions related to knowledge and to cognitive dissonances. Cognition-language-emotional mechanisms operate throughout the hierarchy of the mind and create all higher mental abilities. The review discusses cognitive functions of the beautiful, sublime, music.

  15. Brain potentials predict language selection before speech onset in bilinguals.

    Science.gov (United States)

    Wu, Yan Jing; Thierry, Guillaume

    2017-08-01

    Studies of language production in bilinguals have seldom considered the fact that language selection likely involves proactive control. Here, we show that Chinese-English bilinguals actively inhibit the language not-to-be used before the onset of a picture to be named. Depending on the nature of a directive cue, participants named a subsequent picture in their native language, in their second language, or remained silent. The cue elicited a contingent negative variation of event-related brain potentials, greater in amplitude when the cue announced a naming trial as compared to when it announced a silent trial. In addition, the negativity was greater in amplitude when the picture was to be named in English than in Chinese, suggesting that preparation for speech in the second language requires more inhibition than preparation for speech in the native language. This result is the first direct neurophysiological evidence consistent with proactive inhibitory control in bilingual production. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

  16. Brain tumor segmentation with Deep Neural Networks.

    Science.gov (United States)

    Havaei, Mohammad; Davy, Axel; Warde-Farley, David; Biard, Antoine; Courville, Aaron; Bengio, Yoshua; Pal, Chris; Jodoin, Pierre-Marc; Larochelle, Hugo

    2017-01-01

    In this paper, we present a fully automatic brain tumor segmentation method based on Deep Neural Networks (DNNs). The proposed networks are tailored to glioblastomas (both low and high grade) pictured in MR images. By their very nature, these tumors can appear anywhere in the brain and have almost any kind of shape, size, and contrast. These reasons motivate our exploration of a machine learning solution that exploits a flexible, high capacity DNN while being extremely efficient. Here, we give a description of different model choices that we've found to be necessary for obtaining competitive performance. We explore in particular different architectures based on Convolutional Neural Networks (CNN), i.e. DNNs specifically adapted to image data. We present a novel CNN architecture which differs from those traditionally used in computer vision. Our CNN exploits both local features as well as more global contextual features simultaneously. Also, different from most traditional uses of CNNs, our networks use a final layer that is a convolutional implementation of a fully connected layer which allows a 40 fold speed up. We also describe a 2-phase training procedure that allows us to tackle difficulties related to the imbalance of tumor labels. Finally, we explore a cascade architecture in which the output of a basic CNN is treated as an additional source of information for a subsequent CNN. Results reported on the 2013 BRATS test data-set reveal that our architecture improves over the currently published state-of-the-art while being over 30 times faster. Copyright © 2016 Elsevier B.V. All rights reserved.

  17. Broca Pars Triangularis Constitutes a “Hub” of the Language-Control Network during Simultaneous Language Translation

    Directory of Open Access Journals (Sweden)

    Stefan Elmer

    2016-09-01

    Full Text Available Until now, several branches of research have fundamentally contributed to a better understanding of the ramifications of bilingualism, multilingualism, and language expertise on psycholinguistic-, cognitive-, and neural implications. In this context, it is noteworthy to mention that from a cognitive perspective, there is a strong convergence of data pointing to an influence of multilingual speech competence on a variety of cognitive functions, including attention, short-term- and working memory, set shifting, switching, and inhibition. In addition, complementary neuroimaging findings have highlighted a specific set of cortical and subcortical brain regions which fundamentally contribute to administrate cognitive control in the multilingual brain, namely Broca’s area, the middle-anterior cingulate cortex, the inferior parietal lobe, and the basal ganglia. However, a disadvantage of focusing on group analyses is that this procedure only enables an approximation of the neural networks shared within a population while at the same time smoothing inter-individual differences. In order to address both commonalities (i.e., within group analyses and inter-individual variability (i.e., single-subject analyses in language control mechanisms, here I measured five professional simultaneous interpreters while the participants overtly translated or repeated sentences with a simple subject-verb-object structure. Results demonstrated that pars triangularis was commonly activated across participants during backward translation (i.e., from L2 to L1, whereas the other brain regions of the control network showed a strong inter-individual variability during both backward and forward (i.e., from L1 to L2 translation. Thus, I propose that pars triangularis plays a crucial role within the language-control network and behaves as a fundamental processing entity supporting simultaneous language translation.

  18. Brain networks: small-worlds, after all?

    International Nuclear Information System (INIS)

    Muller, Lyle; Destexhe, Alain; Rudolph-Lilith, Michelle

    2014-01-01

    Since its introduction, the ‘small-world’ effect has played a central role in network science, particularly in the analysis of the complex networks of the nervous system. From the cellular level to that of interconnected cortical regions, many analyses have revealed small-world properties in the networks of the brain. In this work, we revisit the quantification of small-worldness in neural graphs. We find that neural graphs fall into the ‘borderline’ regime of small-worldness, residing close to that of a random graph, especially when the degree sequence of the network is taken into account. We then apply recently introducted analytical expressions for clustering and distance measures, to study this borderline small-worldness regime. We derive theoretical bounds for the minimal and maximal small-worldness index for a given graph, and by semi-analytical means, study the small-worldness index itself. With this approach, we find that graphs with small-worldness equivalent to that observed in experimental data are dominated by their random component. These results provide the first thorough analysis suggesting that neural graphs may reside far away from the maximally small-world regime. (paper)

  19. Abnormal functional lateralization and activity of language brain areas in typical specific language impairment (developmental dysphasia)

    Science.gov (United States)

    De Guibert, Clément; Maumet, Camille; Jannin, Pierre; Ferré, Jean-Christophe; Tréguier, Catherine; Barillot, Christian; Le Rumeur, Elisabeth; Allaire, Catherine; Biraben, Arnaud

    2011-01-01

    Atypical functional lateralization and specialization for language have been proposed to account for developmental language disorders, yet results from functional neuroimaging studies are sparse and inconsistent. This functional magnetic resonance imaging study compared children with a specific subtype of specific language impairment affecting structural language (n=21), to a matched group of typically-developing children using a panel of four language tasks neither requiring reading nor metalinguistic skills, including two auditory lexico-semantic tasks (category fluency and responsive naming) and two visual phonological tasks based on picture naming. Data processing involved normalizing the data with respect to a matched pairs pediatric template, groups and between-groups analysis, and laterality indexes assessment within regions of interest using single and combined task analysis. Children with specific language impairment exhibited a significant lack of left lateralization in all core language regions (inferior frontal gyrus-opercularis, inferior frontal gyrus-triangularis, supramarginal gyrus, superior temporal gyrus), across single or combined task analysis, but no difference of lateralization for the rest of the brain. Between-group comparisons revealed a left hypoactivation of Wernicke’s area at the posterior superior temporal/supramarginal junction during the responsive naming task, and a right hyperactivation encompassing the anterior insula with adjacent inferior frontal gyrus and the head of the caudate nucleus during the first phonological task. This study thus provides evidence that this specific subtype of specific language impairment is associated with atypical lateralization and functioning of core language areas. PMID:21719430

  20. Brain function differences in language processing in children and adults with autism.

    Science.gov (United States)

    Williams, Diane L; Cherkassky, Vladimir L; Mason, Robert A; Keller, Timothy A; Minshew, Nancy J; Just, Marcel Adam

    2013-08-01

    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. © 2013 International Society for Autism Research, Wiley Periodicals, Inc.

  1. Language comprehension and brain function in individuals with an optimal outcome from autism.

    Science.gov (United States)

    Eigsti, Inge-Marie; Stevens, Michael C; Schultz, Robert T; Barton, Marianne; Kelley, Elizabeth; Naigles, Letitia; Orinstein, Alyssa; Troyb, Eva; Fein, Deborah A

    2016-01-01

    Although Autism Spectrum Disorder (ASD) is generally a lifelong disability, a minority of individuals with ASD overcome their symptoms to such a degree that they are generally indistinguishable from their typically-developing peers. That is, they have achieved an Optimal Outcome (OO). The question addressed by the current study is whether this normalized behavior reflects normalized brain functioning, or alternatively, the action of compensatory systems. Either possibility is plausible, as most participants with OO received years of intensive therapy that could alter brain networks to align with typical function or work around ASD-related neural dysfunction. Individuals ages 8 to 21 years with high-functioning ASD (n = 23), OO (n = 16), or typical development (TD; n = 20) completed a functional MRI scan while performing a sentence comprehension task. Results indicated similar activations in frontal and temporal regions (left middle frontal, left supramarginal, and right superior temporal gyri) and posterior cingulate in OO and ASD groups, where both differed from the TD group. Furthermore, the OO group showed heightened "compensatory" activation in numerous left- and right-lateralized regions (left precentral/postcentral gyri, right precentral gyrus, left inferior parietal lobule, right supramarginal gyrus, left superior temporal/parahippocampal gyrus, left middle occipital gyrus) and cerebellum, relative to both ASD and TD groups. Behaviorally normalized language abilities in OO individuals appear to utilize atypical brain networks, with increased recruitment of language-specific as well as right homologue and other systems. Early intensive learning and experience may normalize behavioral language performance in OO, but some brain regions involved in language processing may continue to display characteristics that are more similar to ASD than typical development, while others show characteristics not like ASD or typical development.

  2. Brain basis of childhood speech and language disorders: are we closer to clinically meaningful MRI markers?

    Science.gov (United States)

    Morgan, Angela; Bonthrone, Alexandra; Liégeois, Frédérique J

    2016-12-01

    Developmental speech and language disorders are common, seen in one in 20 preschool children, in the absence of frank neurological deficits or intellectual impairment. They are a key reason parents seek help from paediatricians. Complex neurogenetic and environmental contributions underpin the disorders, yet few specific causes are known. With the advent of quantitative brain imaging, a growing number of studies have investigated neural contributions. Here, we discuss current MRI approaches and recent findings (January 2014-June 2016) in the field. Five relevant studies were identified (n = 3 - speech disorder and n = 2 - language disorder). Significant variability in MRI approaches and heterogeneity of participant phenotypes was seen. Children with speech disorder had structural and functional anomalies in the left supramarginal gyrus and functional anomalies in the posterior cerebellum bilaterally - regions critical for sensory-motor integration or feedback. Children with language disorder showed increased mean and radial diffusivity of the left arcuate fasciculus, although a widespread cortical and subcortical network of regions was implicated. Limited evidence exists for specific regional brain anomalies in this population. MRI prognostic markers of speech and language ability are not currently available at an individual level. Further work is required to disentangle neurobiological contributions to speech and language disorders for affected children.

  3. The elusive concept of brain network. Comment on “Understanding brain networks and brain organization” by Luiz Pessoa

    Science.gov (United States)

    Horwitz, Barry

    2014-09-01

    As the poet John Donne said of man - "No man is an island entire of itself; every man is a piece of the continent, a part of the main." - so the neuroscience research community now says of brain areas. This is the topic that Luiz Pessoa expands upon in his thorough review of the paradigm shift that has occurred in much of brain research, especially in cognitive neuroscience [1]. His key point is made explicitly in the Abstract: "I argue that a network perspective should supplement the common strategy of understanding the brain in terms of individual regions." In his review, Pessoa covers a large range of topics, including how the network perspective changes the way in which one views the structure-function relationship between brain and behavior, the importance of context in ascertaining how a brain region functions, and the notion of emergent properties as a network feature. Also discussed is graph theory, one of the important mathematical methods used to analyze and describe network structure and function.

  4. Structural and functional brain networks: from connections to cognition.

    Science.gov (United States)

    Park, Hae-Jeong; Friston, Karl

    2013-11-01

    How rich functionality emerges from the invariant structural architecture of the brain remains a major mystery in neuroscience. Recent applications of network theory and theoretical neuroscience to large-scale brain networks have started to dissolve this mystery. Network analyses suggest that hierarchical modular brain networks are particularly suited to facilitate local (segregated) neuronal operations and the global integration of segregated functions. Although functional networks are constrained by structural connections, context-sensitive integration during cognition tasks necessarily entails a divergence between structural and functional networks. This degenerate (many-to-one) function-structure mapping is crucial for understanding the nature of brain networks. The emergence of dynamic functional networks from static structural connections calls for a formal (computational) approach to neuronal information processing that may resolve this dialectic between structure and function.

  5. Approach of Complex Networks for the Determination of Brain Death

    International Nuclear Information System (INIS)

    Sun Wei-Gang; Cao Jian-Ting; Wang Ru-Bin

    2011-01-01

    In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our findings might provide valuable insights on the determination of brain death. (cross-disciplinary physics and related areas of science and technology)

  6. Language Model Applications to Spelling with Brain-Computer Interfaces

    Directory of Open Access Journals (Sweden)

    Anderson Mora-Cortes

    2014-03-01

    Full Text Available Within the Ambient Assisted Living (AAL community, Brain-Computer Interfaces (BCIs have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies.

  7. Language model applications to spelling with Brain-Computer Interfaces.

    Science.gov (United States)

    Mora-Cortes, Anderson; Manyakov, Nikolay V; Chumerin, Nikolay; Van Hulle, Marc M

    2014-03-26

    Within the Ambient Assisted Living (AAL) community, Brain-Computer Interfaces (BCIs) have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion) have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies.

  8. Mental arithmetic in the bilingual brain: Language matters.

    Science.gov (United States)

    Van Rinsveld, Amandine; Dricot, Laurence; Guillaume, Mathieu; Rossion, Bruno; Schiltz, Christine

    2017-07-01

    How do bilinguals solve arithmetic problems in each of their languages? We investigated this question by exploring the neural substrates of mental arithmetic in bilinguals. Critically, our population was composed of a homogeneous group of adults who were fluent in both of their instruction languages (i.e., German as first instruction language and French as second instruction language). Twenty bilinguals were scanned with fMRI (3T) while performing mental arithmetic. Both simple and complex problems were presented to disentangle memory retrieval occuring in very simple problems from arithmetic computation occuring in more complex problems. In simple additions, the left temporal regions were more activated in German than in French, whereas no brain regions showed additional activity in the reverse constrast. Complex additions revealed the reverse pattern, since the activations of regions for French surpassed the same computations in German and the extra regions were located predominantly in occipital regions. Our results thus highlight that highly proficient bilinguals rely on differential activation patterns to solve simple and complex additions in each of their languages, suggesting different solving procedures. The present study confirms the critical role of language in arithmetic problem solving and provides novel insights into how highly proficient bilinguals solve arithmetic problems. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. The Influence of Japanese Anime Language to Chinese Network Buzzwords

    Directory of Open Access Journals (Sweden)

    Cai Jin Chang

    2016-01-01

    Full Text Available In this paper, the influence of Japanese anime language to Chinese network buzzwords was studied, and the maturity and rigor were quoted. The Japanese anime language refined, creative can be so popular in the factors of psychologies also was analyzed. According to these studies, some suggestions were put forward that how to standardize the network buzzwords and how to raise its taste.

  10. Recognition of sign language gestures using neural networks

    Directory of Open Access Journals (Sweden)

    Simon Vamplew

    2007-04-01

    Full Text Available This paper describes the structure and performance of the SLARTI sign language recognition system developed at the University of Tasmania. SLARTI uses a modular architecture consisting of multiple feature-recognition neural networks and a nearest-neighbour classifier to recognise Australian sign language (Auslan hand gestures.

  11. Recognition of sign language gestures using neural networks

    OpenAIRE

    Simon Vamplew

    2007-01-01

    This paper describes the structure and performance of the SLARTI sign language recognition system developed at the University of Tasmania. SLARTI uses a modular architecture consisting of multiple feature-recognition neural networks and a nearest-neighbour classifier to recognise Australian sign language (Auslan) hand gestures.

  12. Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence.

    Directory of Open Access Journals (Sweden)

    Kai Wu

    Full Text Available Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.

  13. Brain-based origins of change language: a beginning.

    Science.gov (United States)

    Feldstein Ewing, Sarah W; Yezhuvath, Uma; Houck, Jon M; Filbey, Francesca M

    2014-12-01

    Motivational interviewing (MI) is a promising treatment for heavy drinking. Client change talk (CT), a critical component of MI, has been associated with differential brain activation. The goal of this study was to begin to deconstruct how and why CT may affect the brain. Specifically, we sought to determine whether simply repeating statements in favor of change would cause differential brain activation, or whether client statements must be spontaneously generated within a therapeutic milieu in order to influence brain activation. We therefore examined blood oxygenation level dependent (BOLD) response following two types of client language (CT; and sustain talk, ST) across two conditions: (1) Self-Generated: CT and ST were elicited during an MI session vs. (2) Experimenter-Selected: a pre-established list of CT and ST was provided to the individual in the absence of an MI session. Across both conditions, participants' CT and ST were visually and aurally presented during fMRI. We enrolled 39 recent binge drinkers (41% male; M age=19.9; n=18 in Self-Generated group; n=21 in Experimenter-Selected group). We found that both types of client language (CT and ST) elicited greater BOLD activation in the Self-Generated vs. the Experimenter-Selected group in the left inferior frontal gyrus/anterior insula and superior temporal gyri (p≤0.001). These findings indicate that the nature of client language matters. It appears that it is not just the words themselves, but the origin (naturally generated within a therapeutic session) that influences brain-based effects. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Language representation in the human brain: evidence from cortical mapping.

    Science.gov (United States)

    Bhatnagar, S C; Mandybur, G T; Buckingham, H W; Andy, O J

    2000-09-01

    The manner in which the human brain processes grammatical-syntactic and lexical-semantic functions has been extensively debated in neurolinguistics. The discreteness and selectivity of the representation of syntactic-morphological properties in the dominant frontal cortex and the representation of the lexical-semantics in the temporo-parietal cortex have been questioned. Three right-handed adult male neurosurgical patients undergoing left craniotomy for intractable seizures were evaluated using various grammatical and semantic tasks during cortical mapping. The sampling of language tasks consisted of trials with stimulation (experimental) and without stimulation (control) from sites in the dominant fronto-temporo-parietal cortex The sampling of language implicated a larger cortical area devoted to language (syntactic-morphological and lexical-semantic) tasks. Further, a large part of the fronto-parieto-temporal cortex was involved with syntactic-morphological functions. However, only the parieto-temporal sites were implicated with the ordering of lexicon in sentence construction. These observations suggest that the representation of language in the human brain may be columnar or multilayered. Copyright 2000 Academic Press.

  15. The shape of the language-ready brain

    Directory of Open Access Journals (Sweden)

    Cedric Arnaud Boeckx

    2014-04-01

    Full Text Available Our core hypothesis is that the emergence of our species-specific language-ready brain ought to be understood in light of the developmental changes expressed at the levels of brain morphology and neural connectivity that occurred in our species after the split from Neanderthals-Denisovans and that gave us a more globular braincase configuration. In addition to changes at the cortical level, we hypothesize that the anatomical shift that led to globularity also entailed significant changes at the subcortical level. We claim that the functional consequences of such changes must also be taken into account to gain a fuller understanding of our linguistic capacity. Here we focus on the thalamus, which we argue is central to language and human cognition, as it modulates fronto-parietal activity. With this new neurobiological perspective in place, we examine its possible molecular basis. We construct a candidate gene set whose members are involved in the development and connectivity of the thalamus, in the evolution of the human head, and are known to give rise to language-associated cognitive disorders. We submit that the new gene candidate set opens up new windows into our understanding of the genetic basis of our linguistic capacity. Thus, our hypothesis aims at generating new testing grounds concerning core aspects of language ontogeny and phylogeny.

  16. Switching Language Modes: Complementary Brain Patterns for Formulaic and Propositional Language.

    Science.gov (United States)

    Sidtis, John J; Van Lancker Sidtis, Diana; Dhawan, Vijay; Eidelberg, David

    2018-04-01

    Language has been modeled as a rule governed behavior for generating an unlimited number of novel utterances using phonological, syntactic, and lexical processes. This view of language as essentially propositional is expanding as a contributory role of formulaic expressions (e.g., you know, have a nice day, how are you?) is increasingly recognized. The basic features of the functional anatomy of this language system have been described by studies of brain damage: left lateralization for propositional language and greater right lateralization and basal ganglia involvement for formulaic expressions. Positron emission tomography (PET) studies of cerebral blood flow (CBF) have established a cortical-subcortical pattern of brain activity predictive of syllable rate during phonological/lexical repetition. The same analytic approach was applied to analyzing brain images obtained during spontaneous monologues. Sixteen normal, right-handed, native English speakers underwent PET scanning during several language tasks. Speech rate for the repetition of phonological/lexical items was predicted by increased CBF in the left inferior frontal region and decreased CBF in the head of the right caudate nucleus, replicating previous results. A complementary cortical-subcortical pattern (CBF increased in the right inferior frontal region and decreased in the left caudate) was predictive of the use of speech formulas during monologue speech. The use of propositional language during the monologues was associated with strong left lateralization (increased CBF at the left inferior frontal region and decreased CBF at the right inferior frontal region). Normal communication involves the integration of two language modes, formulaic and novel, that have different neural substrates.

  17. Language and reading development in the brain today: neuromarkers and the case for prediction.

    Science.gov (United States)

    Buchweitz, Augusto

    2016-01-01

    The goal of this article is to provide an account of language development in the brain using the new information about brain function gleaned from cognitive neuroscience. This account goes beyond describing the association between language and specific brain areas to advocate the possibility of predicting language outcomes using brain-imaging data. The goal is to address the current evidence about language development in the brain and prediction of language outcomes. Recent studies will be discussed in the light of the evidence generated for predicting language outcomes and using new methods of analysis of brain data. The present account of brain behavior will address: (1) the development of a hardwired brain circuit for spoken language; (2) the neural adaptation that follows reading instruction and fosters the "grafting" of visual processing areas of the brain onto the hardwired circuit of spoken language; and (3) the prediction of language development and the possibility of translational neuroscience. Brain imaging has allowed for the identification of neural indices (neuromarkers) that reflect typical and atypical language development; the possibility of predicting risk for language disorders has emerged. A mandate to develop a bridge between neuroscience and health and cognition-related outcomes may pave the way for translational neuroscience. Copyright © 2016 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

  18. The neurophysiology of language: Insights from non-invasive brain stimulation in the healthy human brain.

    Science.gov (United States)

    Hartwigsen, Gesa

    2015-09-01

    With the advent of non-invasive brain stimulation (NIBS), a new decade in the study of language has started. NIBS allows for testing the functional relevance of language-related brain activation and enables the researcher to investigate how neural activation changes in response to focal perturbations. This review focuses on the application of NIBS in the healthy brain. First, some basic mechanisms will be introduced and the prerequisites for carrying out NIBS studies of language are addressed. The next section outlines how NIBS can be used to characterize the contribution of the stimulated area to a task. In this context, novel approaches such as multifocal transcranial magnetic stimulation and the condition-and-perturb approach are discussed. The third part addresses the combination of NIBS and neuroimaging in the study of plasticity. These approaches are particularly suited to investigate short-term reorganization in the healthy brain and may inform models of language recovery in post-stroke aphasia. Copyright © 2014 The Author. Published by Elsevier Inc. All rights reserved.

  19. Pediatric traumatic brain injury: language outcomes and their relationship to the arcuate fasciculus.

    Science.gov (United States)

    Liégeois, Frédérique J; Mahony, Kate; Connelly, Alan; Pigdon, Lauren; Tournier, Jacques-Donald; Morgan, Angela T

    2013-12-01

    Pediatric traumatic brain injury (TBI) may result in long-lasting language impairments alongside dysarthria, a motor-speech disorder. Whether this co-morbidity is due to the functional links between speech and language networks, or to widespread damage affecting both motor and language tracts, remains unknown. Here we investigated language function and diffusion metrics (using diffusion-weighted tractography) within the arcuate fasciculus, the uncinate fasciculus, and the corpus callosum in 32 young people after TBI (approximately half with dysarthria) and age-matched healthy controls (n=17). Only participants with dysarthria showed impairments in language, affecting sentence formulation and semantic association. In the whole TBI group, sentence formulation was best predicted by combined corpus callosum and left arcuate volumes, suggesting this "dual blow" seriously reduces the potential for functional reorganisation. Word comprehension was predicted by fractional anisotropy in the right arcuate. The co-morbidity between dysarthria and language deficits therefore seems to be the consequence of multiple tract damage. Copyright © 2013 Elsevier Inc. All rights reserved.

  20. A comparison of brain activity associated with language production in brain tumor patients with left and right sided language laterality.

    Science.gov (United States)

    Jansma, J M; Ramsey, N; Rutten, G J

    2015-12-01

    Language dominance is an important factor for clinical decision making in brain tumor surgery. Functional MRI can provide detailed information about the organization of language in the brain. One often used measure derived from fMRI data is the laterality index (LI). The LI is typically based on the ratio between left and right brain activity in a specific region associated with language. Nearly all fMRI language studies show language-related activity in both hemispheres, and as a result the LI shows a large range of values. The clinical significance of the variation in language laterality as measured with the LI is still under debate. In this study, we tested two hypotheses in relation to the LI, measured in Broca's region, and it's right hemisphere homologue: 1: the level of activity in Broca's and it's right hemisphere homologue is mirrored for subjects with an equal but opposite LI; 2: the whole brain language activation pattern differs between subjects with an equal but opposite LI. One hundred sixty-three glioma and meningioma patients performed a verb generation task as part of a standard clinical protocol. We calculated the LI in the pars orbitalis, pars triangularis and pars opercularis of the left inferior frontal gyrus, referred to as Broca's region from here on. In our database, 21 patients showed right lateralized activity, with a moderate average level (-0.32). A second group of 21 patients was selected from the remaining group, for equal but opposite LI (0.32). We compared the level and distribution of activity associated with language production in the left and right hemisphere in these two groups. Patients with left sided laterality showed a significantly higher level of activity in Broca's region than the patients with right sided laterality. However, both groups showed no difference in level of activity in Broca's homologue region in the right hemisphere. Also, we did not see any difference in the pattern of activity between patients with left

  1. Abnormal neural activities of directional brain networks in patients with long-term bilateral hearing loss.

    Science.gov (United States)

    Xu, Long-Chun; Zhang, Gang; Zou, Yue; Zhang, Min-Feng; Zhang, Dong-Sheng; Ma, Hua; Zhao, Wen-Bo; Zhang, Guang-Yu

    2017-10-13

    The objective of the study is to provide some implications for rehabilitation of hearing impairment by investigating changes of neural activities of directional brain networks in patients with long-term bilateral hearing loss. Firstly, we implemented neuropsychological tests of 21 subjects (11 patients with long-term bilateral hearing loss, and 10 subjects with normal hearing), and these tests revealed significant differences between the deaf group and the controls. Then we constructed the individual specific virtual brain based on functional magnetic resonance data of participants by utilizing effective connectivity and multivariate regression methods. We exerted the stimulating signal to the primary auditory cortices of the virtual brain and observed the brain region activations. We found that patients with long-term bilateral hearing loss presented weaker brain region activations in the auditory and language networks, but enhanced neural activities in the default mode network as compared with normally hearing subjects. Especially, the right cerebral hemisphere presented more changes than the left. Additionally, weaker neural activities in the primary auditor cortices were also strongly associated with poorer cognitive performance. Finally, causal analysis revealed several interactional circuits among activated brain regions, and these interregional causal interactions implied that abnormal neural activities of the directional brain networks in the deaf patients impacted cognitive function.

  2. Complex brain networks: From topological communities to clustered ...

    Indian Academy of Sciences (India)

    Abstract. Recent research has revealed a rich and complicated network topology in the cortical connectivity of mammalian brains. A challenging task is to understand the implications of such network structures on the functional organisation of the brain activ- ities. We investigate synchronisation dynamics on the ...

  3. Potential brain language reorganization in a boy with refractory epilepsy; an fNIRS–EEG and fMRI comparison

    Directory of Open Access Journals (Sweden)

    Phetsamone Vannasing

    2016-01-01

    Full Text Available As part of a presurgical investigation for a resection of a tumor located in the left temporal brain region, we evaluated pre- and postsurgical language lateralization in a right-handed boy with refractory epilepsy. In this study, we compared functional near infrared spectroscopy (fNIRS results obtained while the participant performed expressive and receptive language tasks with those obtained using functional magnetic resonance imaging (fMRI. This case study illustrates the potential for NIRS to contribute favorably to the localization of language functions in children with epilepsy and cognitive or behavioral problems and its potential advantages over fMRI in presurgical assessment. Moreover, it suggests that fNIRS is sensitive in localizing an atypical language network or potential brain reorganization related to epilepsy in young patients.

  4. Mapping human whole-brain structural networks with diffusion MRI.

    Directory of Open Access Journals (Sweden)

    Patric Hagmann

    Full Text Available Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world.

  5. The Brain Network Underpinning Novel Melody Creation.

    Science.gov (United States)

    Adhikari, Bhim M; Norgaard, Martin; Quinn, Kristen M; Ampudia, Jenine; Squirek, Justin; Dhamala, Mukesh

    2016-12-01

    Musical improvisation offers an excellent experimental paradigm for the study of real-time human creativity. It involves moment-to-moment decision-making, monitoring of one's performance, and utilizing external feedback to spontaneously create new melodies or variations on a melody. Recent neuroimaging studies have begun to study the brain activity during musical improvisation, aiming to unlock the mystery of human creativity. What brain resources come together and how these are utilized during musical improvisation are not well understood. To help answer these questions, we recorded electroencephalography (EEG) signals from 19 experienced musicians while they played or imagined short isochronous learned melodies and improvised on those learned melodies. These four conditions (Play-Prelearned, Play-Improvised, Imagine-Prelearned, Imagine-Improvised) were randomly interspersed in a total of 300 trials per participant. From the sensor-level EEG, we found that there were power differences in the alpha (8-12 Hz) and beta (13-30 Hz) bands in separate clusters of frontal, parietal, temporal, and occipital electrodes. Using EEG source localization and dipole modeling methods for task-related signals, we identified the locations and network activities of five sources: the left superior frontal gyrus (L SFG), supplementary motor area (SMA), left inferior parietal lobule (L IPL), right dorsolateral prefrontal cortex, and right superior temporal gyrus. During improvisation, the network activity between L SFG, SMA, and L IPL was significantly less than during the prelearned conditions. Our results support the general idea that attenuated cognitive control facilitates the production of creative output.

  6. Second language acquisition after traumatic brain injury: a case study.

    Science.gov (United States)

    Połczyńska-Fiszer, M; Mazaux, J M

    2008-01-01

    Post-traumatic language and memory impairment, as well as a subsequent recovery in monolinguals have been widely documented in the literature, yet little is known about learning the second language after a severe head trauma followed by coma, as well as the relationship of this process with cognitive recovery, psychological status and quality of life. The present study investigates the relationship of learning the second language (English) in the process of rehabilitation, with quality of life in a Polish female university student who, as a result of a car accident, suffered a major closed-head injury and was comatose for a month. The subject was enrolled in an English learning program nine months after the trauma. The experiment lasted six months and comprised monthly meetings. The patient improved the major components of the second language, including vocabulary. Within the 6 months, the subject was gradually capable of learning additional and more complex lexical items. Learning the second language after traumatic brain injury may positively influence emotional well-being, self-esteem, and, perhaps, recovery of quality of life. A long-term beneficial effect of learning L2 was a consequential improvement of the patient's memory.

  7. Brain-on-a-chip integrated neuronal networks

    NARCIS (Netherlands)

    Xie, Sijia

    2016-01-01

    The brain-on-a-chip technology aims to provide an efficient and economic in vitro platform for brain disease study. In the well-known literature on brain-on-a-chip systems, nonstructured surfaces were conventionally used for the cell attachment in a culture chamber, therefore the neuronal networks

  8. Brain white matter structure and language ability in preschool-aged children.

    Science.gov (United States)

    Walton, Matthew; Dewey, Deborah; Lebel, Catherine

    2018-01-01

    Brain alterations are associated with reading and language difficulties in older children, but little research has investigated relationships between early language skills and brain white matter structure during the preschool period. We studied 68 children aged 3.0-5.6 years who underwent diffusion tensor imaging and participated in assessments of Phonological Processing and Speeded Naming. Tract-based spatial statistics and tractography revealed relationships between Phonological Processing and diffusion parameters in bilateral ventral white matter pathways and the corpus callosum. Phonological Processing was positively correlated with fractional anisotropy and negatively correlated with mean diffusivity. The relationships observed in left ventral pathways are consistent with studies in older children, and demonstrate that structural markers for language performance are apparent as young as 3 years of age. Our findings in right hemisphere areas that are not as commonly found in adult studies suggest that young children rely on a widespread network for language processing that becomes more specialized with age. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Dual Language Use in Sign-Speech Bimodal Bilinguals: fNIRS Brain-Imaging Evidence

    Science.gov (United States)

    Kovelman, Ioulia; Shalinsky, Mark H.; White, Katherine S.; Schmitt, Shawn N.; Berens, Melody S.; Paymer, Nora; Petitto, Laura-Ann

    2009-01-01

    The brain basis of bilinguals' ability to use two languages at the same time has been a hotly debated topic. On the one hand, behavioral research has suggested that bilingual dual language use involves complex and highly principled linguistic processes. On the other hand, brain-imaging research has revealed that bilingual language switching…

  10. High Proficiency in a Second Language is Characterized by Greater Involvement of the First Language Network: Evidence from Chinese Learners of English

    Science.gov (United States)

    Cao, Fan; Tao, Ran; Liu, Li; Perfetti, Charles A.; Booth, James R.

    2014-01-01

    The assimilation hypothesis argues that second language learning recruits the brain network for processing the native language, whereas the accommodation hypothesis argues that learning a second language recruits brain structures not involved in native language processing. This study tested these hypotheses by examining brain activation of a group of native Chinese speakers, who were late bilinguals with varying levels of proficiency in English, when they performed a rhyming judgment to visually presented English word pairs (CE group) during fMRI. Assimilation was examined by comparing the CE group to native Chinese speakers performing the rhyming task in Chinese (CC group), and accommodation was examined by comparing the CE group to native English speakers performing the rhyming task in English (EE group). The CE group was very similar in activation to the CC group, supporting the assimilation hypothesis. Additional support for the assimilation hypothesis was the finding that higher proficiency in the CE group was related to increased activation in the Chinese network (as defined by the CC > EE), including the left middle frontal gyrus, the right inferior parietal lobule, and the right precuneus, and decreased activation in the English network (as defined by the EE > CC), including the left inferior frontal gyrus and the left inferior temporal gyrus. Although most of the results support assimilation, there was some evidence for accommodation as the CE group showed less activation in the Chinese network including the right middle occipital gyrus, which has been argued to be involved in holistic visuospatial processing of Chinese characters. PMID:23654223

  11. Resolving structural variability in network models and the brain.

    Directory of Open Access Journals (Sweden)

    Florian Klimm

    2014-03-01

    Full Text Available Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity do not in general simultaneously display a second (e.g., hierarchy. This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful

  12. MaLT - Combined Motor and Language Therapy Tool for Brain Injury Patients Using Kinect.

    Science.gov (United States)

    Wairagkar, Maitreyee; McCrindle, Rachel; Robson, Holly; Meteyard, Lotte; Sperrin, Malcom; Smith, Andy; Pugh, Moyra

    2017-03-23

    The functional connectivity and structural proximity of elements of the language and motor systems result in frequent co-morbidity post brain injury. Although rehabilitation services are becoming increasingly multidisciplinary and "integrated", treatment for language and motor functions often occurs in isolation. Thus, behavioural therapies which promote neural reorganisation do not reflect the high intersystem connectivity of the neurologically intact brain. As such, there is a pressing need for rehabilitation tools which better reflect and target the impaired cognitive networks. The objective of this research is to develop a combined high dosage therapy tool for language and motor rehabilitation. The rehabilitation therapy tool developed, MaLT (Motor and Language Therapy), comprises a suite of computer games targeting both language and motor therapy that use the Kinect sensor as an interaction device. The games developed are intended for use in the home environment over prolonged periods of time. In order to track patients' engagement with the games and their rehabilitation progress, the game records patient performance data for the therapist to interrogate. MaLT incorporates Kinect-based games, a database of objects and language parameters, and a reporting tool for therapists. Games have been developed that target four major language therapy tasks involving single word comprehension, initial phoneme identification, rhyme identification and a naming task. These tasks have 8 levels each increasing in difficulty. A database of 750 objects is used to programmatically generate appropriate questions for the game, providing both targeted therapy and unique gameplay every time. The design of the games has been informed by therapists and by discussions with a Public Patient Involvement (PPI) group. Pilot MaLT trials have been conducted with three stroke survivors for the duration of 6 to 8 weeks. Patients' performance is monitored through MaLT's reporting facility

  13. Genomic connectivity networks based on the BrainSpan atlas of the developing human brain

    Science.gov (United States)

    Mahfouz, Ahmed; Ziats, Mark N.; Rennert, Owen M.; Lelieveldt, Boudewijn P. F.; Reinders, Marcel J. T.

    2014-03-01

    The human brain comprises systems of networks that span the molecular, cellular, anatomic and functional levels. Molecular studies of the developing brain have focused on elucidating networks among gene products that may drive cellular brain development by functioning together in biological pathways. On the other hand, studies of the brain connectome attempt to determine how anatomically distinct brain regions are connected to each other, either anatomically (diffusion tensor imaging) or functionally (functional MRI and EEG), and how they change over development. A global examination of the relationship between gene expression and connectivity in the developing human brain is necessary to understand how the genetic signature of different brain regions instructs connections to other regions. Furthermore, analyzing the development of connectivity networks based on the spatio-temporal dynamics of gene expression provides a new insight into the effect of neurodevelopmental disease genes on brain networks. In this work, we construct connectivity networks between brain regions based on the similarity of their gene expression signature, termed "Genomic Connectivity Networks" (GCNs). Genomic connectivity networks were constructed using data from the BrainSpan Transcriptional Atlas of the Developing Human Brain. Our goal was to understand how the genetic signatures of anatomically distinct brain regions relate to each other across development. We assessed the neurodevelopmental changes in connectivity patterns of brain regions when networks were constructed with genes implicated in the neurodevelopmental disorder autism (autism spectrum disorder; ASD). Using graph theory metrics to characterize the GCNs, we show that ASD-GCNs are relatively less connected later in development with the cerebellum showing a very distinct expression of ASD-associated genes compared to other brain regions.

  14. Hyper-connectivity of functional networks for brain disease diagnosis.

    Science.gov (United States)

    Jie, Biao; Wee, Chong-Yaw; Shen, Dinggang; Zhang, Daoqiang

    2016-08-01

    Exploring structural and functional interactions among various brain regions enables better understanding of pathological underpinnings of neurological disorders. Brain connectivity network, as a simplified representation of those structural and functional interactions, has been widely used for diagnosis and classification of neurodegenerative diseases, especially for Alzheimer's disease (AD) and its early stage - mild cognitive impairment (MCI). However, the conventional functional connectivity network is usually constructed based on the pairwise correlation among different brain regions and thus ignores their higher-order relationships. Such loss of high-order information could be important for disease diagnosis, since neurologically a brain region predominantly interacts with more than one other brain regions. Accordingly, in this paper, we propose a novel framework for estimating the hyper-connectivity network of brain functions and then use this hyper-network for brain disease diagnosis. Here, the functional connectivity hyper-network denotes a network where each of its edges representing the interactions among multiple brain regions (i.e., an edge can connect with more than two brain regions), which can be naturally represented by a hyper-graph. Specifically, we first construct connectivity hyper-networks from the resting-state fMRI (R-fMRI) time series by using sparse representation. Then, we extract three sets of brain-region specific features from the connectivity hyper-networks, and further exploit a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Finally, we use multi-kernel support vector machine (SVM) for classification. The experimental results on both MCI dataset and attention deficit hyperactivity disorder (ADHD) dataset demonstrate that, compared with the conventional connectivity network-based methods, the proposed method can not only improve the classification performance, but also help

  15. Effects of thalamic deep brain stimulation on spontaneous language production.

    Science.gov (United States)

    Ehlen, Felicitas; Vonberg, Isabelle; Kühn, Andrea A; Klostermann, Fabian

    2016-08-01

    The thalamus is thought to contribute to language-related processing, but specifications of this notion remain vague. An assessment of potential effects of thalamic deep brain stimulation (DBS) on spontaneous language may help to delineate respective functions. For this purpose, we analyzed spontaneous language samples from thirteen (six female / seven male) patients with essential tremor treated with DBS of the thalamic ventral intermediate nucleus (VIM) in their respective ON vs. OFF conditions. Samples were obtained from semi-structured interviews and examined on multidimensional linguistic levels. In the VIM-DBS ON condition, participants used a significantly higher proportion of paratactic as opposed to hypotactic sentence structures. This increase correlated negatively with the change in the more global cognitive score, which in itself did not change significantly. In conclusion, VIM-DBS appears to induce the use of a simplified syntactic structure. The findings are discussed in relation to concepts of thalamic roles in language-related cognitive behavior. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. Complex brain networks: From topological communities to clustered ...

    Indian Academy of Sciences (India)

    Complex brain networks: From topological communities to clustered dynamics ... http://www.ias.ac.in/article/fulltext/pram/070/06/1087-1097 ... We find that this network of networks displays clustered synchronisation behaviour and the dynamical clusters closely coincide with the topological community structures observed in ...

  17. Evidence for hubs in human functional brain networks.

    Science.gov (United States)

    Power, Jonathan D; Schlaggar, Bradley L; Lessov-Schlaggar, Christina N; Petersen, Steven E

    2013-08-21

    Hubs integrate and distribute information in powerful ways due to the number and positioning of their contacts in a network. Several resting-state functional connectivity MRI reports have implicated regions of the default mode system as brain hubs; we demonstrate that previous degree-based approaches to hub identification may have identified portions of large brain systems rather than critical nodes of brain networks. We utilize two methods to identify hub-like brain regions: (1) finding network nodes that participate in multiple subnetworks of the brain, and (2) finding spatial locations in which several systems are represented within a small volume. These methods converge on a distributed set of regions that differ from previous reports on hubs. This work identifies regions that support multiple systems, leading to spatially constrained predictions about brain function that may be tested in terms of lesions, evoked responses, and dynamic patterns of activity. Copyright © 2013 Elsevier Inc. All rights reserved.

  18. Age of second language acquisition in multilinguals has an impact on grey matter volume in language-associated brain areas

    OpenAIRE

    Anelis eKaiser; Sara Leila eEppenberger; Renata eSmieskova; Stefan eBorgwardt; Esther eKuenzli; Erstn-Wilhelm eRadue; Cordula eNitsch; Kerstin eBendfeldt

    2015-01-01

    Numerous structural studies have established that experience shapes and reshapes the brain throughout a lifetime. The impact of early development, however, is still a matter of debate. Further clues may come from studying multilinguals who acquired their second language at different ages. We investigated adult multilinguals who spoke three languages fluently, where the third language was learned in classroom settings, not before the age of 9 years. Multilinguals exposed to two languages simul...

  19. A network of genes, genetic disorders, and brain areas.

    Directory of Open Access Journals (Sweden)

    Satoru Hayasaka

    Full Text Available The network-based approach has been used to describe the relationship among genes and various phenotypes, producing a network describing complex biological relationships. Such networks can be constructed by aggregating previously reported associations in the literature from various databases. In this work, we applied the network-based approach to investigate how different brain areas are associated to genetic disorders and genes. In particular, a tripartite network with genes, genetic diseases, and brain areas was constructed based on the associations among them reported in the literature through text mining. In the resulting network, a disproportionately large number of gene-disease and disease-brain associations were attributed to a small subset of genes, diseases, and brain areas. Furthermore, a small number of brain areas were found to be associated with a large number of the same genes and diseases. These core brain regions encompassed the areas identified by the previous genome-wide association studies, and suggest potential areas of focus in the future imaging genetics research. The approach outlined in this work demonstrates the utility of the network-based approach in studying genetic effects on the brain.

  20. A network of genes, genetic disorders, and brain areas.

    Science.gov (United States)

    Hayasaka, Satoru; Hugenschmidt, Christina E; Laurienti, Paul J

    2011-01-01

    The network-based approach has been used to describe the relationship among genes and various phenotypes, producing a network describing complex biological relationships. Such networks can be constructed by aggregating previously reported associations in the literature from various databases. In this work, we applied the network-based approach to investigate how different brain areas are associated to genetic disorders and genes. In particular, a tripartite network with genes, genetic diseases, and brain areas was constructed based on the associations among them reported in the literature through text mining. In the resulting network, a disproportionately large number of gene-disease and disease-brain associations were attributed to a small subset of genes, diseases, and brain areas. Furthermore, a small number of brain areas were found to be associated with a large number of the same genes and diseases. These core brain regions encompassed the areas identified by the previous genome-wide association studies, and suggest potential areas of focus in the future imaging genetics research. The approach outlined in this work demonstrates the utility of the network-based approach in studying genetic effects on the brain.

  1. Role of physical and mental training in brain network configuration

    Directory of Open Access Journals (Sweden)

    Philip P. Foster

    2015-06-01

    Full Text Available Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of energy cost-driven small-world network disorder as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement produces a reconfiguration of brain networks into greater small-worldness. Creation of synaptic connections in a macro-network, and, at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF. The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brainbrain in such trainings? What is the respective role of independent mental, physical or combined-mental-physical trainings? Physical practice seems to be playing an instrumental role in the cognitive enhancement (brain ↔ muscle com.. However, mental training, meditation or virtual reality (films, games require only minimal motor activity and cardio-respiratory stimulation. Therefore, other potential paths (brainbrain com. molding brain networks are nonetheless essential. Patients with motor neuron disease/injury (e.g. amyotrophic lateral sclerosis, traumatism also achieve successful cognitive enhancement albeit they may only elicit mental practice

  2. Brain and Cognitive Reserve: Translation via Network Control Theory

    Science.gov (United States)

    Medaglia, John Dominic; Pasqualetti, Fabio; Hamilton, Roy H.; Thompson-Schill, Sharon L.; Bassett, Danielle S.

    2017-01-01

    Traditional approaches to understanding the brain’s resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive “reserve,” associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity in the human brain. We describe the theoretical opportunities offered by the application of network control theory at the level of the human connectome to understand cognitive resilience and inform translational intervention. PMID:28104411

  3. Brain and Social Networks: Fundamental Building Blocks of Human Experience.

    Science.gov (United States)

    Falk, Emily B; Bassett, Danielle S

    2017-09-01

    How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Diagnostic work up for language testing in patients undergoing awake craniotomy for brain lesions in language areas.

    Science.gov (United States)

    Bilotta, Federico; Stazi, Elisabetta; Titi, Luca; Lalli, Diana; Delfini, Roberto; Santoro, Antonio; Rosa, Giovanni

    2014-06-01

    Awake craniotomy is the technique of choice in patients with brain tumours adjacent to primary and accessory language areas (Broca's and Wernicke's areas). Language testing should be aimed to detect preoperative deficits, to promptly identify the occurrence of new intraoperative impairments and to establish the course of postoperative language status. Aim of this case series is to describe our experience with a dedicated language testing work up to evaluate patients with or at risk for language disturbances undergoing awake craniotomy for brain tumour resection. Pre- and intra operative testing was accomplished with 8 tests. Intraoperative evaluation was accomplished when patients were fully cooperative (Ramsey language testings were normal in 9 patients (45%), showed mild to moderate language deficit in 8 (40%) and severe language deficit or aphasic disorders in 3 (15%). Broca's area was identified in 15 patients, in all cases by counting arrest during stimulation and in 12 cases by naming arrest. In this article we describe our experience using a language testing work up to evaluate - pre, intra and postoperatively - patients undergoing awake craniotomy for brain tumour resection with preoperative language disturbances or at risk for postoperative language deficits. This approach allows a systematic evaluation and recording of language function status and can be accomplished even when a neuropsychologist or speech therapist are not involved in the operation crew.

  5. Mother's Social Network and Family Language Maintenance

    Science.gov (United States)

    Velazquez, Isabel

    2013-01-01

    This article reports the results of a social network analysis (SNA) performed on the mother's primary network of interaction in 15 Mexican American families in the city of El Paso, Texas, the neighbourhood of La Villita, in Chicago, and the city of Lincoln, Nebraska. The goal of this study was to examine potential opportunities for Spanish use by…

  6. Scalable Brain Network Construction on White Matter Fibers.

    Science.gov (United States)

    Chung, Moo K; Adluru, Nagesh; Dalton, Kim M; Alexander, Andrew L; Davidson, Richard J

    2011-02-12

    DTI offers a unique opportunity to characterize the structural connectivity of the human brain non-invasively by tracing white matter fiber tracts. Whole brain tractography studies routinely generate up to half million tracts per brain, which serves as edges in an extremely large 3D graph with up to half million edges. Currently there is no agreed-upon method for constructing the brain structural network graphs out of large number of white matter tracts. In this paper, we present a scalable iterative framework called the ε-neighbor method for building a network graph and apply it to testing abnormal connectivity in autism.

  7. Scalable brain network construction on white matter fibers

    Science.gov (United States)

    Chung, Moo K.; Adluru, Nagesh; Dalton, Kim M.; Alexander, Andrew L.; Davidson, Richard J.

    2011-03-01

    DTI offers a unique opportunity to characterize the structural connectivity of the human brain non-invasively by tracing white matter fiber tracts. Whole brain tractography studies routinely generate up to half million tracts per brain, which serves as edges in an extremely large 3D graph with up to half million edges. Currently there is no agreed-upon method for constructing the brain structural network graphs out of large number of white matter tracts. In this paper, we present a scalable iterative framework called the ɛ-neighbor method for building a network graph and apply it to testing abnormal connectivity in autism.

  8. Functional connectivity in task-negative network of the Deaf: effects of sign language experience

    Directory of Open Access Journals (Sweden)

    Evie Malaia

    2014-06-01

    Full Text Available Prior studies investigating cortical processing in Deaf signers suggest that life-long experience with sign language and/or auditory deprivation may alter the brain’s anatomical structure and the function of brain regions typically recruited for auditory processing (Emmorey et al., 2010; Pénicaud et al., 2013 inter alia. We report the first investigation of the task-negative network in Deaf signers and its functional connectivity—the temporal correlations among spatially remote neurophysiological events. We show that Deaf signers manifest increased functional connectivity between posterior cingulate/precuneus and left medial temporal gyrus (MTG, but also inferior parietal lobe and medial temporal gyrus in the right hemisphere- areas that have been found to show functional recruitment specifically during sign language processing. These findings suggest that the organization of the brain at the level of inter-network connectivity is likely affected by experience with processing visual language, although sensory deprivation could be another source of the difference. We hypothesize that connectivity alterations in the task negative network reflect predictive/automatized processing of the visual signal.

  9. Brain Networks Implicated in Seasonal Affective Disorder

    DEFF Research Database (Denmark)

    Nørgaard, Martin; Ganz, Melanie; Svarer, Claus

    2017-01-01

    , patients with SAD fail to globally downregulate their cerebral serotonin transporter (5-HTT) in winter, and that this effect seemed to be particularly pronounced in female S-carriers of the 5-HTTLPR genotype. The purpose of this study was to identify a 5-HTT brain network that accounts for the adaption...... to the environmental stressor of winter in females with the short 5-HTTLPR genotype, a specific subgroup previously reported to be at increased risk for developing SAD. Methods: Nineteen females, either S' carriers (LG- and S-carriers) without SAD (N = 13, mean age 23.6 ± 3.2 year, range 19-28) or S' carriers with SAD...... (N = 6, mean age 23.7 ± 2.4, range 21-26) were PET-scanned with [11C]DASB during both summer and winter seasons (asymptomatic and symptomatic phase, 38 scans in total) in randomized order, defined as a 12-week interval centered on summer or winter solstice. We used a multivariate Partial Least...

  10. Development of large-scale functional brain networks in children.

    Directory of Open Access Journals (Sweden)

    Kaustubh Supekar

    2009-07-01

    Full Text Available The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y and 22 young-adults (ages 19-22 y. Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

  11. Social Network Development, Language Use, and Language Acquisition during Study Abroad: Arabic Language Learners' Perspectives

    Science.gov (United States)

    Dewey, Dan P.; Belnap, R. Kirk; Hillstrom, Rebecca

    2013-01-01

    Language learners and educators have subscribed to the belief that those who go abroad will have many opportunities to use the target language and will naturally become proficient. They also assume that language learners will develop relationships with native speakers allowing them to use the language and become more fluent, an assumption…

  12. Role of physical and mental training in brain network configuration.

    Science.gov (United States)

    Foster, Philip P

    2015-01-01

    It is hypothesized that the topology of brain networks is constructed by connecting nodes which may be continuously remodeled by appropriate training. Efficiency of physical and/or mental training on the brain relies on the flexibility of networks' architecture molded by local remodeling of proteins and synapses of excitatory neurons producing transformations in network topology. Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of "energy cost-driven small-world network disorder" with dysfunction of high-energy cost wiring as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement, presumably via reconfiguration of brain networks into greater small-worldness, appears essential in learning, memory, and executive functions. A macroscopic cartography of creation-removal of synaptic connections in a macro-network, and at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF). The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brainbrain in such trainings? What is the respective role of independent mental, physical, or combined-mental-physical trainings? Physical practice seems to be

  13. Nutritional status, brain network organization, and general intelligence.

    Science.gov (United States)

    Zamroziewicz, Marta K; Talukdar, M Tanveer; Zwilling, Chris E; Barbey, Aron K

    2017-11-01

    The high energy demands of the brain underscore the importance of nutrition in maintaining brain health and further indicate that aspects of nutrition may optimize brain health, in turn enhancing cognitive performance. General intelligence represents a critical cognitive ability that has been well characterized by cognitive neuroscientists and psychologists alike, but the extent to which a driver of brain health, namely nutritional status, impacts the neural mechanisms that underlie general intelligence is not understood. This study therefore examined the relationship between the intrinsic connectivity networks supporting general intelligence and nutritional status, focusing on nutrients known to impact the metabolic processes that drive brain function. We measured general intelligence, favorable connective architecture of seven intrinsic connectivity networks, and seventeen plasma phospholipid monounsaturated and saturated fatty acids in a sample of 99 healthy, older adults. A mediation analysis was implemented to investigate the relationship between empirically derived patterns of fatty acids, general intelligence, and underlying intrinsic connectivity networks. The mediation analysis revealed that small world propensity within one intrinsic connectivity network supporting general intelligence, the dorsal attention network, was promoted by a pattern of monounsaturated fatty acids. These results suggest that the efficiency of functional organization within a core network underlying general intelligence is influenced by nutritional status. This report provides a novel connection between nutritional status and functional network efficiency, and further supports the promise and utility of functional connectivity metrics in studying the impact of nutrition on cognitive and brain health. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Age of second language acquisition in multilinguals has an impact on grey matter volume in language-associated brain areas

    Directory of Open Access Journals (Sweden)

    Anelis eKaiser

    2015-06-01

    Full Text Available Numerous structural studies have established that experience shapes and reshapes the brain throughout a lifetime. The impact of early development, however, is still a matter of debate. Further clues may come from studying multilinguals who acquired their second language at different ages. We investigated adult multilinguals who spoke three languages fluently, where the third language was learned in classroom settings, not before the age of 9 years. Multilinguals exposed to 2 languages simultaneously from birth (SiM were contrasted with multinguals who acquired their first two languages successively (SuM. Whole brain voxel based morphometry revealed that, relative to SuM, SiM have significantly lower grey matter volume in several language-associated cortical areas in both hemispheres: bilaterally in medial and inferior frontal gyrus, in the right medial temporal gyrus and inferior posterior parietal gyrus, as well as in the left inferior frontal gyrus. Thus, as shown by others, successive language learning increases the volume of language-associated cortical areas. In brains exposed early on and simultaneously to more than one language, however, learning of additional languages seems to have less impact. We conclude that - at least with respect to language acquisition - early developmental influences are maintained and influence experience-dependent plasticity well into adulthood.

  15. Age of second language acquisition in multilinguals has an impact on gray matter volume in language-associated brain areas.

    Science.gov (United States)

    Kaiser, Anelis; Eppenberger, Leila S; Smieskova, Renata; Borgwardt, Stefan; Kuenzli, Esther; Radue, Ernst-Wilhelm; Nitsch, Cordula; Bendfeldt, Kerstin

    2015-01-01

    Numerous structural studies have established that experience shapes and reshapes the brain throughout a lifetime. The impact of early development, however, is still a matter of debate. Further clues may come from studying multilinguals who acquired their second language at different ages. We investigated adult multilinguals who spoke three languages fluently, where the third language was learned in classroom settings, not before the age of 9 years. Multilinguals exposed to two languages simultaneously from birth (SiM) were contrasted with multinguals who acquired their first two languages successively (SuM). Whole brain voxel based morphometry revealed that, relative to SuM, SiM have significantly lower gray matter volume in several language-associated cortical areas in both hemispheres: bilaterally in medial and inferior frontal gyrus, in the right medial temporal gyrus and inferior posterior parietal gyrus, as well as in the left inferior temporal gyrus. Thus, as shown by others, successive language learning increases the volume of language-associated cortical areas. In brains exposed early on and simultaneously to more than one language, however, learning of additional languages seems to have less impact. We conclude that - at least with respect to language acquisition - early developmental influences are maintained and have an effect on experience-dependent plasticity well into adulthood.

  16. Brain functional plasticity associated with the emergence of expertise in extreme language control.

    Science.gov (United States)

    Hervais-Adelman, Alexis; Moser-Mercer, Barbara; Golestani, Narly

    2015-07-01

    We used functional magnetic resonance imaging (fMRI) to longitudinally examine brain plasticity arising from long-term, intensive simultaneous interpretation training. Simultaneous interpretation is a bilingual task with heavy executive control demands. We compared brain responses observed during simultaneous interpretation with those observed during simultaneous speech repetition (shadowing) in a group of trainee simultaneous interpreters, at the beginning and at the end of their professional training program. Age, sex and language-proficiency matched controls were scanned at similar intervals. Using multivariate pattern classification, we found distributed patterns of changes in functional responses from the first to second scan that distinguished the interpreters from the controls. We also found reduced recruitment of the right caudate nucleus during simultaneous interpretation as a result of training. Such practice-related change is consistent with decreased demands on multilingual language control as the task becomes more automatized with practice. These results demonstrate the impact of simultaneous interpretation training on the brain functional response in a cerebral structure that is not specifically linguistic, but that is known to be involved in learning, in motor control, and in a variety of domain-general executive functions. Along with results of recent studies showing functional and structural adaptations in the caudate nuclei of experts in a broad range of domains, our results underline the importance of this structure as a central node in expertise-related networks. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. Episodic memory in aspects of large-scale brain networks

    Directory of Open Access Journals (Sweden)

    Woorim eJeong

    2015-08-01

    Full Text Available Understanding human episodic memory in aspects of large-scale brain networks has become one of the central themes in neuroscience over the last decade. Traditionally, episodic memory was regarded as mostly relying on medial temporal lobe (MTL structures. However, recent studies have suggested involvement of more widely distributed cortical network and the importance of its interactive roles in the memory process. Both direct and indirect neuro-modulations of the memory network have been tried in experimental treatments of memory disorders. In this review, we focus on the functional organization of the MTL and other neocortical areas in episodic memory. Task-related neuroimaging studies together with lesion studies suggested that specific sub-regions of the MTL are responsible for specific components of memory. However, recent studies have emphasized that connectivity within MTL structures and even their network dynamics with other cortical areas are essential in the memory process. Resting-state functional network studies also have revealed that memory function is subserved by not only the MTL system but also a distributed network, particularly the default-mode network. Furthermore, researchers have begun to investigate memory networks throughout the entire brain not restricted to the specific resting-state network. Altered patterns of functional connectivity among distributed brain regions were observed in patients with memory impairments. Recently, studies have shown that brain stimulation may impact memory through modulating functional networks, carrying future implications of a novel interventional therapy for memory impairment.

  18. Episodic memory in aspects of large-scale brain networks

    Science.gov (United States)

    Jeong, Woorim; Chung, Chun Kee; Kim, June Sic

    2015-01-01

    Understanding human episodic memory in aspects of large-scale brain networks has become one of the central themes in neuroscience over the last decade. Traditionally, episodic memory was regarded as mostly relying on medial temporal lobe (MTL) structures. However, recent studies have suggested involvement of more widely distributed cortical network and the importance of its interactive roles in the memory process. Both direct and indirect neuro-modulations of the memory network have been tried in experimental treatments of memory disorders. In this review, we focus on the functional organization of the MTL and other neocortical areas in episodic memory. Task-related neuroimaging studies together with lesion studies suggested that specific sub-regions of the MTL are responsible for specific components of memory. However, recent studies have emphasized that connectivity within MTL structures and even their network dynamics with other cortical areas are essential in the memory process. Resting-state functional network studies also have revealed that memory function is subserved by not only the MTL system but also a distributed network, particularly the default-mode network (DMN). Furthermore, researchers have begun to investigate memory networks throughout the entire brain not restricted to the specific resting-state network (RSN). Altered patterns of functional connectivity (FC) among distributed brain regions were observed in patients with memory impairments. Recently, studies have shown that brain stimulation may impact memory through modulating functional networks, carrying future implications of a novel interventional therapy for memory impairment. PMID:26321939

  19. Small-World Propensity and Weighted Brain Networks.

    Science.gov (United States)

    Muldoon, Sarah Feldt; Bridgeford, Eric W; Bassett, Danielle S

    2016-02-25

    Quantitative descriptions of network structure can provide fundamental insights into the function of interconnected complex systems. Small-world structure, diagnosed by high local clustering yet short average path length between any two nodes, promotes information flow in coupled systems, a key function that can differ across conditions or between groups. However, current techniques to quantify small-worldness are density dependent and neglect important features such as the strength of network connections, limiting their application in real-world systems. Here, we address both limitations with a novel metric called the Small-World Propensity (SWP). In its binary instantiation, the SWP provides an unbiased assessment of small-world structure in networks of varying densities. We extend this concept to the case of weighted brain networks by developing (i) a standardized procedure for generating weighted small-world networks, (ii) a weighted extension of the SWP, and (iii) a method for mapping observed brain network data onto the theoretical model. In applying these techniques to compare real-world brain networks, we uncover the surprising fact that the canonical biological small-world network, the C. elegans neuronal network, has strikingly low SWP. These metrics, models, and maps form a coherent toolbox for the assessment and comparison of architectural properties in brain networks.

  20. A permutation testing framework to compare groups of brain networks

    Directory of Open Access Journals (Sweden)

    Sean L Simpson

    2013-11-01

    Full Text Available Brain network analyses have moved to the forefront of neuroimaging research over the last decade. However, methods for statistically comparing groups of networks have lagged behind. These comparisons have great appeal for researchers interested in gaining further insight into complex brain function and how it changes across different mental states and disease conditions. Current comparison approaches generally either rely on a summary metric or on mass-univariate nodal or edge-based comparisons that ignore the inherent topological properties of the network, yielding little power and failing to make network level comparisons. Gleaning deeper insights into normal and abnormal changes in complex brain function demands methods that take advantage of the wealth of data present in an entire brain network. Here we propose a permutation testing framework that allows comparing groups of networks while incorporating topological features inherent in each individual network. We validate our approach using simulated data with known group differences. We then apply the method to functional brain networks derived from fMRI data.

  1. A functional MRI study of language networks in left medial temporal lobe epilepsy

    International Nuclear Information System (INIS)

    Yu Aihong; Wang Xiaoyi; Xu Guoqing; Li Yongjie; Qin Wen; Li Kuncheng; Wang, Yuping

    2011-01-01

    Purpose: The purpose of this study was to investigate the abnormality of language networks in left medial temporal lobe epilepsy (MTLE) using fMRI. Materials and methods: Eight patients with left MTLE and 15 healthy subjects were evaluated. An auditory semantic judgment (AJ) paradigm was used. The fMRI data were collected on a 3T MR system and analyzed by AFNI (analysis of functional neuroimages) to generate the activation map. Results: Behavioral data showed that the reaction time of the left MTLE patients was significantly longer than that of controls on the AJ task (t = -3.396, P < 0.05). The left MTLE patients also exhibited diffusively decreased activation in the AJ task. Right hemisphere dominance of Broca's and Wernicke's areas was demonstrated in left MTLE patients. Conclusions: Long-term activation of spikes in left MTLE patients results in language impairment, which is associated with an abnormality of the brain neural network.

  2. The hippocampus: hub of brain network communication for memory.

    NARCIS (Netherlands)

    Battaglia, F.P.; Benchenane, K.; Sirota, A.; Pennartz, C.M.A.; Wiener, S.I.

    2011-01-01

    A complex brain network, centered on the hippocampus, supports episodic memories throughout their lifetimes. Classically, upon memory encoding during active behavior, hippocampal activity is dominated by theta oscillations (6-10Hz). During inactivity, hippocampal neurons burst synchronously,

  3. Neuronal networks in the developing brain are adversely modulated by early psychosocial neglect.

    Science.gov (United States)

    Stamoulis, Catherine; Vanderwert, Ross E; Zeanah, Charles H; Fox, Nathan A; Nelson, Charles A

    2017-10-01

    The brain's neural circuitry plays a ubiquitous role across domains in cognitive processing and undergoes extensive reorganization during the course of development in part as a result of experience. In this study we investigated the effects of profound early psychosocial neglect associated with institutional rearing on the development of task-independent brain networks, estimated from longitudinally acquired electroencephalographic (EEG) data from networks were identified in children that had been reared in institutions: 1 ) a hyperconnected parieto-occipital network, which included cortical hubs and connections that may partially overlap with default-mode network, and 2 ) a hypoconnected network between left temporal and distributed bilateral regions, both of which were aberrantly connected across neural oscillations. This study provides the first evidence of the adverse effects of early psychosocial neglect on the wiring of the developing brain. Given these networks' potentially significant role in various cognitive processes, including memory, learning, social communication, and language, these findings suggest that institutionalization in early life may profoundly impact the neural correlates underlying multiple cognitive domains, in ways that may not be fully reversible in the short term. NEW & NOTEWORTHY This paper provides first evidence that early psychosocial neglect associated with institutional rearing profoundly affects the development of the brain's neural circuitry. Using longitudinally acquired electrophysiological data from the Bucharest Early Intervention Project (BEIP), the paper identifies multiple task-independent networks that are abnormally connected (hyper- or hypoconnected) in children reared in institutions compared with never-institutionalized children. These networks involve spatially distributed brain areas and their abnormal connections may adversely impact neural information processing across cognitive domains. Copyright © 2017 the

  4. Unmasking Language Lateralization in Human Brain Intrinsic Activity

    Science.gov (United States)

    McAvoy, Mark; Mitra, Anish; Coalson, Rebecca S.; d'Avossa, Giovanni; Keidel, James L.; Petersen, Steven E.; Raichle, Marcus E.

    2016-01-01

    Lateralization of function is a fundamental feature of the human brain as exemplified by the left hemisphere dominance of language. Despite the prominence of lateralization in the lesion, split-brain and task-based fMRI literature, surprisingly little asymmetry has been revealed in the increasingly popular functional imaging studies of spontaneous fluctuations in the fMRI BOLD signal (so-called resting-state fMRI). Here, we show the global signal, an often discarded component of the BOLD signal in resting-state studies, reveals a leftward asymmetry that maps onto regions preferential for semantic processing in left frontal and temporal cortex and the right cerebellum and a rightward asymmetry that maps onto putative attention-related regions in right frontal, temporoparietal, and parietal cortex. Hemispheric asymmetries in the global signal resulted from amplitude modulation of the spontaneous fluctuations. To confirm these findings obtained from normal, healthy, right-handed subjects in the resting-state, we had them perform 2 semantic processing tasks: synonym and numerical magnitude judgment and sentence comprehension. In addition to establishing a new technique for studying lateralization through functional imaging of the resting-state, our findings shed new light on the physiology of the global brain signal. PMID:25636911

  5. Brain signatures of artificial language processing: evidence challenging the critical period hypothesis.

    Science.gov (United States)

    Friederici, Angela D; Steinhauer, Karsten; Pfeifer, Erdmut

    2002-01-08

    Adult second language learning seems to be more difficult and less efficient than first language acquisition during childhood. By using event-related brain potentials, we show that adults who learned a miniature artificial language display a similar real-time pattern of brain activation when processing this language as native speakers do when processing natural languages. Participants trained in the artificial language showed two event-related brain potential components taken to reflect early automatic and late controlled syntactic processes, whereas untrained participants did not. This result challenges the common view that late second language learners process language in a principally different way from native speakers. Our findings demonstrate that a small system of grammatical rules can be syntactically instantiated by the adult speaker in a way that strongly resembles native-speaker sentence processing.

  6. Mapping Critical Language Sites in Children Performing Verb Generation: Whole-Brain Connectivity and Graph Theoretical Analysis in MEG.

    Science.gov (United States)

    Youssofzadeh, Vahab; Williamson, Brady J; Kadis, Darren S

    2017-01-01

    A classic left frontal-temporal brain network is known to support language processes. However, the level of participation of constituent regions, and the contribution of extra-canonical areas, is not fully understood; this is particularly true in children, and in individuals who have experienced early neurological insult. In the present work, we propose whole-brain connectivity and graph-theoretical analysis of magnetoencephalography (MEG) source estimates to provide robust maps of the pediatric expressive language network. We examined neuromagnetic data from a group of typically-developing young children ( n = 15, ages 4-6 years) and adolescents ( n = 14, 16-18 years) completing an auditory verb generation task in MEG. All source analyses were carried out using a linearly-constrained minimum-variance (LCMV) beamformer. Conventional differential analyses revealed significant ( p EVC) . Hub analysis revealed the importance of left perisylvian sites, i.e., Broca's and Wernicke's areas, across groups. The hemispheric distribution of frontal and temporal lobe EVC values was asymmetrical in most subjects; left dominant EVC was observed in 20% of young children, and 71% of adolescents. Interestingly, the adolescent group demonstrated increased critical sites in the right cerebellum, left inferior frontal gyrus (IFG) and left putamen. Here, we show that whole brain connectivity and network analysis can be used to map critical language sites in typical development; these methods may be useful for defining the margins of eloquent tissue in neurosurgical candidates.

  7. Learners' Attitudes toward Foreign Language Practice on Social Network Sites

    Science.gov (United States)

    Villafuerte, Jhonny; Romero, Asier

    2017-01-01

    This work aims to study learners' attitudes towards practicing English Language on Social Networks Sites (SNS). The sample involved 110 students from the University Laica Eloy Alfaro de Manabi in Ecuador, and the University of the Basque Country in Spain. The instrument applied was a Likert scale questionnaire designed Ad hoc by the researchers,…

  8. Recurrent Artificial Neural Networks and Finite State Natural Language Processing.

    Science.gov (United States)

    Moisl, Hermann

    It is argued that pessimistic assessments of the adequacy of artificial neural networks (ANNs) for natural language processing (NLP) on the grounds that they have a finite state architecture are unjustified, and that their adequacy in this regard is an empirical issue. First, arguments that counter standard objections to finite state NLP on the…

  9. Language Learning through Social Networks: Perceptions and Reality

    Science.gov (United States)

    Lin, Chin-Hsi; Warschauer, Mark; Blake, Robert

    2016-01-01

    Language Learning Social Network Sites (LLSNSs) have attracted millions of users around the world. However, little is known about how people participate in these sites and what they learn from them. This study investigated learners' attitudes, usage, and progress in a major LLSNS through a survey of 4,174 as well as 20 individual case studies. The…

  10. Business Process Modeling Languages Supporting Collaborative Networks

    NARCIS (Netherlands)

    Soleimani Malekan, H.; Afsarmanesh, H.; Hammoudi, S.; Maciaszek, L.A.; Cordeiro, J.; Dietz, J.L.G.

    2013-01-01

    Formalizing the definition of Business Processes (BPs) performed within each enterprise is fundamental for effective deployment of their competencies and capabilities within Collaborative Networks (CN). In our approach, every enterprise in the CN is represented by its set of BPs, so that other

  11. Automatic classification of schizophrenia using resting-state functional language network via an adaptive learning algorithm

    Science.gov (United States)

    Zhu, Maohu; Jie, Nanfeng; Jiang, Tianzi

    2014-03-01

    A reliable and precise classification of schizophrenia is significant for its diagnosis and treatment of schizophrenia. Functional magnetic resonance imaging (fMRI) is a novel tool increasingly used in schizophrenia research. Recent advances in statistical learning theory have led to applying pattern classification algorithms to access the diagnostic value of functional brain networks, discovered from resting state fMRI data. The aim of this study was to propose an adaptive learning algorithm to distinguish schizophrenia patients from normal controls using resting-state functional language network. Furthermore, here the classification of schizophrenia was regarded as a sample selection problem where a sparse subset of samples was chosen from the labeled training set. Using these selected samples, which we call informative vectors, a classifier for the clinic diagnosis of schizophrenia was established. We experimentally demonstrated that the proposed algorithm incorporating resting-state functional language network achieved 83.6% leaveone- out accuracy on resting-state fMRI data of 27 schizophrenia patients and 28 normal controls. In contrast with KNearest- Neighbor (KNN), Support Vector Machine (SVM) and l1-norm, our method yielded better classification performance. Moreover, our results suggested that a dysfunction of resting-state functional language network plays an important role in the clinic diagnosis of schizophrenia.

  12. Functional Brain Network Mechanism of Hypersensitivity in Chronic Pain.

    Science.gov (United States)

    Lee, UnCheol; Kim, Minkyung; Lee, KyoungEun; Kaplan, Chelsea M; Clauw, Daniel J; Kim, Seunghwan; Mashour, George A; Harris, Richard E

    2018-01-10

    Fibromyalgia (FM) is a chronic widespread pain condition characterized by augmented multi-modal sensory sensitivity. Although the mechanisms underlying this sensitivity are thought to involve an imbalance in excitatory and inhibitory activity throughout the brain, the underlying neural network properties associated with hypersensitivity to pain stimuli are largely unknown. In network science, explosive synchronization (ES) was introduced as a mechanism of hypersensitivity in diverse biological and physical systems that display explosive and global propagations with small perturbations. We hypothesized that ES may also be a mechanism of the hypersensitivity in FM brains. To test this hypothesis, we analyzed resting state electroencephalogram (EEG) of 10 FM patients. First, we examined theoretically well-known ES conditions within functional brain networks reconstructed from EEG, then tested whether a brain network model with ES conditions identified in the EEG data is sensitive to an external perturbation. We demonstrate for the first time that the FM brain displays characteristics of ES conditions, and that these factors significantly correlate with chronic pain intensity. The simulation data support the conclusion that networks with ES conditions are more sensitive to perturbation compared to non-ES network. The model and empirical data analysis provide convergent evidence that ES may be a network mechanism of FM hypersensitivity.

  13. Resection of highly language-eloquent brain lesions based purely on rTMS language mapping without awake surgery.

    Science.gov (United States)

    Ille, Sebastian; Sollmann, Nico; Butenschoen, Vicki M; Meyer, Bernhard; Ringel, Florian; Krieg, Sandro M

    2016-12-01

    The resection of left-sided perisylvian brain lesions harbours the risk of postoperative language impairment. Therefore the individual patient's language distribution is investigated by intraoperative direct cortical stimulation (DCS) during awake surgery. Yet, not all patients qualify for awake surgery. Non-invasive language mapping by repetitive navigated transcranial magnetic stimulation (rTMS) has frequently shown a high correlation in comparison with the results of DCS language mapping in terms of language-negative brain regions. The present study analyses the extent of resection (EOR) and functional outcome of patients who underwent left-sided perisylvian resection of brain lesions based purely on rTMS language mapping. Four patients with left-sided perisylvian brain lesions (two gliomas WHO III, one glioblastoma, one cavernous angioma) underwent rTMS language mapping prior to surgery. Data from rTMS language mapping and rTMS-based diffusion tensor imaging fibre tracking (DTI-FT) were transferred to the intraoperative neuronavigation system. Preoperatively, 5 days after surgery (POD5), and 3 months after surgery (POM3) clinical follow-up examinations were performed. No patient suffered from a new surgery-related aphasia at POM3. Three patients underwent complete resection immediately, while one patient required a second rTMS-based resection some days later to achieve the final, complete resection. The present study shows for the first time the feasibility of successfully resecting language-eloquent brain lesions based purely on the results of negative language maps provided by rTMS language mapping and rTMS-based DTI-FT. In very select cases, this technique can provide a rescue strategy with an optimal functional outcome and EOR when awake surgery is not feasible.

  14. Commonality of neural representations of sentences across languages: Predicting brain activation during Portuguese sentence comprehension using an English-based model of brain function.

    Science.gov (United States)

    Yang, Ying; Wang, Jing; Bailer, Cyntia; Cherkassky, Vladimir; Just, Marcel Adam

    2017-02-01

    The aim of the study was to test the cross-language generative capability of a model that predicts neural activation patterns evoked by sentence reading, based on a semantic characterization of the sentence. In a previous study on English monolingual speakers (Wang et al., submitted), a computational model performed a mapping from a set of 42 concept-level semantic features (Neurally Plausible Semantic Features, NPSFs) as well as 6 thematic role markers to neural activation patterns (assessed with fMRI), to predict activation levels in a network of brain locations. The model used two types of information gained from the English-based fMRI data to predict the activation for individual sentences in Portuguese. First, it used the mapping weights from NPSFs to voxel activation levels derived from the model for English reading. Second, the brain locations for which the activation levels were predicted were derived from a factor analysis of the brain activation patterns during English reading. These meta-language locations were defined by the clusters of voxels with high loadings on each of the four main dimensions (factors), namely people, places, actions and feelings, underlying the neural representations of the stimulus sentences. This cross-language model succeeded in predicting the brain activation patterns associated with the reading of 60 individual Portuguese sentences that were entirely new to the model, attaining accuracies reliably above chance level. The prediction accuracy was not affected by whether the Portuguese speaker was monolingual or Portuguese-English bilingual. The model's confusion errors indicated an accurate capture of the events or states described in the sentence at a conceptual level. Overall, the cross-language predictive capability of the model demonstrates the neural commonality between speakers of different languages in the representations of everyday events and states, and provides an initial characterization of the common meta-language

  15. Language Development and Brain Magnetic Resonance Imaging Characteristics in Preschool Children with Cerebral Palsy

    Science.gov (United States)

    Choi, Ja Young; Choi, Yoon Seong; Park, Eun Sook

    2017-01-01

    Purpose: The purpose of this study was to investigate characteristics of language development in relation to brain magnetic resonance imaging (MRI) characteristics and the other contributing factors to language development in children with cerebral palsy (CP). Method: The study included 172 children with CP who underwent brain MRI and language…

  16. From the Left to the Right: How the Brain Compensates Progressive Loss of Language Function

    Science.gov (United States)

    Thiel, Alexander; Habedank, Birgit; Herholz, Karl; Kessler, Josef; Winhuisen, Lutz; Haupt, Walter F.; Heiss, Wolf-Dieter

    2006-01-01

    In normal right-handed subjects language production usually is a function of the left brain hemisphere. Patients with aphasia following brain damage to the left hemisphere have a considerable potential to compensate for the loss of this function. Sometimes, but not always, areas of the right hemisphere which are homologous to language areas of the…

  17. Brain Network Analysis from High-Resolution EEG Signals

    Science.gov (United States)

    de Vico Fallani, Fabrizio; Babiloni, Fabio

    Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular

  18. Free Language Selection in the Bilingual Brain: An Event-Related fMRI Study

    Science.gov (United States)

    Zhang, Yong; Wang, Tao; Huang, Peiyu; Li, Dan; Qiu, Jiang; Shen, Tong; Xie, Peng

    2015-01-01

    Bilingual speakers may select between two languages either on demand (forced language selection) or on their own volition (free language selection). However, the neural substrates underlying free and forced language selection may differ. While the neural substrates underlying forced language selection have been well-explored with language switching paradigms, those underlying free language selection have remained unclear. Using a modified digit-naming switching paradigm, we addressed the neural substrates underlying free language selection by contrasting free language switching with forced language switching. For a digit-pair trial, Chinese-English bilinguals named each digit in Chinese or English either on demand under forced language selection condition or on their own volition under free language selection condition. The results revealed activation in the frontoparietal regions that mediate volition of language selection. Furthermore, a comparison of free and forced language switching demonstrated differences in the patterns of brain activation. Additionally, free language switching showed reduced switching costs as compared to forced language switching. These findings suggest differences between the mechanism(s) underlying free and forced language switching. As such, the current study suggests interactivity between control of volition and control of language switching in free language selection, providing insights into a model of bilingual language control. PMID:26177885

  19. Neuroimaging of the bilingual brain: Structural brain correlates of listening and speaking in a second language.

    Science.gov (United States)

    Kuhl, Patricia K; Stevenson, Jeff; Corrigan, Neva M; van den Bosch, Jasper J F; Can, Dilara Deniz; Richards, Todd

    2016-11-01

    Diffusion tensor imaging was used to compare white matter structure between American monolingual and Spanish-English bilingual adults living in the United States. In the bilingual group, relationships between white matter structure and naturalistic immersive experience in listening to and speaking English were additionally explored. White matter structural differences between groups were found to be bilateral and widespread. In the bilingual group, experience in listening to English was more robustly correlated with decreases in radial and mean diffusivity in anterior white matter regions of the left hemisphere, whereas experience in speaking English was more robustly correlated with increases in fractional anisotropy in more posterior left hemisphere white matter regions. The findings suggest that (a) foreign language immersion induces neuroplasticity in the adult brain, (b) the degree of alteration is proportional to language experience, and (c) the modes of immersive language experience have more robust effects on different brain regions and on different structural features. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  20. Write to read: the brain's universal reading and writing network.

    Science.gov (United States)

    Perfetti, Charles A; Tan, Li-Hai

    2013-02-01

    Do differences in writing systems translate into differences in the brain's reading network? Or is this network universal, relatively impervious to variation in writing systems? A new study adds intriguing evidence to these questions by showing that reading handwritten words activates a pre-motor area across writing systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. Optimal Brain Surgeon on Artificial Neural Networks in

    DEFF Research Database (Denmark)

    Christiansen, Niels Hørbye; Job, Jonas Hultmann; Klyver, Katrine

    2012-01-01

    It is shown how the procedure know as optimal brain surgeon can be used to trim and optimize artificial neural networks in nonlinear structural dynamics. Beside optimizing the neural network, and thereby minimizing computational cost in simulation, the surgery procedure can also serve as a quick ...

  2. Identification and classification of hubs in brain networks.

    NARCIS (Netherlands)

    Sporns, O.; Honey, C.J.; Kotter, R.

    2007-01-01

    Brain regions in the mammalian cerebral cortex are linked by a complex network of fiber bundles. These inter-regional networks have previously been analyzed in terms of their node degree, structural motif, path length and clustering coefficient distributions. In this paper we focus on the

  3. Recurrent Temporal Networks and Language Acquisition – From Corticostriatal Neurophysiology to Reservoir Computing

    Directory of Open Access Journals (Sweden)

    Peter Ford Dominey

    2013-08-01

    Full Text Available One of the most paradoxical aspects of human language is that it is so unlike any other form of behavior in the animal world, yet at the same time, it has developed in a species that is not far removed from ancestral species that do not possess language. While aspects of non-human primate and avian interaction clearly constitute communication, this communication appears distinct from the rich, combinatorial and abstract quality of human language. So how does the human primate brain allow for language? In an effort to answer this question, a line of research has been developed that attempts to build a language processing capability based in part on the gross neuroanatomy of the corticostriatal system of the human brain. This paper situates this research program in its historical context, that begins with the primate oculomotor system and sensorimotor sequencing, and passes, via recent advances in reservoir computing to provide insight into the open questions, and possible approaches, for future research that attempts to model language processing. One novel and useful idea from this research is that the overlap of cortical projections onto common regions in the striatum allows for adaptive binding of cortical signals from distinct circuits, under the control of dopamine, which has a strong adaptive advantage. A second idea is that recurrent networks with fixed connections can represent arbitrary sequential and temporal structure, which is the basis of the reservoir computing framework. Finally, bringing these notions together, a relatively simple mechanism can be built for learning the grammatical constructions, as the mappings from surface structure of sentences to their meaning. This research suggests that the components of language that link conceptual structure to grammatical structure may be much simpler that has been proposed in other research programs. It also suggests that part of the residual complexity is in the conceptual system itself.

  4. Preservation of structural brain network hubs is associated with less severe post-stroke aphasia.

    Science.gov (United States)

    Gleichgerrcht, Ezequiel; Kocher, Madison; Nesland, Travis; Rorden, Chris; Fridriksson, Julius; Bonilha, Leonardo

    2015-01-01

    Post-stroke aphasia is typically associated with ischemic damage to cortical areas or with loss of connectivity among spared brain regions. It remains unclear whether the participation of spared brain regions as networks hubs affects the severity of aphasia. We evaluated language performance and magnetic resonance imaging from 44 participants with chronic aphasia post-stroke. The individual structural brain connectomes were constructed from diffusion tensor. Hub regions were defined in accordance with the rich club classification and studied in relation with language performance. Number of remaining left hemisphere rich club nodes was associated with aphasia, including comprehension, repetition and naming sub-scores. Importantly, among participants with relative preservation of regions of interest for language, aphasia severity was lessened if the region was not only spared, but also participated in the remaining network as a rich club node: Brodmann area (BA) 44/45 - repetition (p = 0.009), BA 39 - repetition (p = 0.045) and naming (p hubs is directly associated with aphasia severity after stroke.

  5. Functional Connectivity Hubs and Networks in the Awake Marmoset Brain.

    Science.gov (United States)

    Belcher, Annabelle M; Yen, Cecil Chern-Chyi; Notardonato, Lucia; Ross, Thomas J; Volkow, Nora D; Yang, Yihong; Stein, Elliot A; Silva, Afonso C; Tomasi, Dardo

    2016-01-01

    In combination with advances in analytical methods, resting-state fMRI is allowing unprecedented access to a better understanding of the network organization of the brain. Increasing evidence suggests that this architecture may incorporate highly functionally connected nodes, or "hubs", and we have recently proposed local functional connectivity density (lFCD) mapping to identify highly-connected nodes in the human brain. Here, we imaged awake nonhuman primates to test whether, like the human brain, the marmoset brain contains FC hubs. Ten adult common marmosets (Callithrix jacchus) were acclimated to mild, comfortable restraint using individualized helmets. Following restraint training, resting BOLD data were acquired during eight consecutive 10 min scans for each subject. lFCD revealed prominent cortical and subcortical hubs of connectivity across the marmoset brain; specifically, in primary and secondary visual cortices (V1/V2), higher-order visual association areas (A19M/V6[DM]), posterior parietal and posterior cingulate areas (PGM and A23b/A31), thalamus, dorsal and ventral striatal areas (caudate, putamen, lateral septal nucleus, and anterior cingulate cortex (A24a). lFCD hubs were highly connected to widespread areas of the brain, and further revealed significant network-network interactions. These data provide a baseline platform for future investigations in a nonhuman primate model of the brain's network topology.

  6. Disrupted Brain Network Hubs in Subtype-Specific Parkinson's Disease.

    Science.gov (United States)

    Ma, Ling-Yan; Chen, Xiao-Dan; He, Yong; Ma, Hui-Zi; Feng, Tao

    2017-01-01

    The topological organization of brain functional networks is impaired in Parkinson's disease (PD). However, the altered patterns of functional network hubs in different subtypes of PD are not completely understood. 3T resting-state functional MRI and voxel-based graph-theory analysis were employed to systematically investigate the intrinsic functional connectivity patterns of whole-brain networks. We enrolled 31 patients with PD (12 tremor dominant [TD] and 19 with postural instability/gait difficulty [PIGD]) and 22 matched healthy controls. Whole-brain voxel-wise functional networks were constructed by measuring the temporal correlations of each pair of brain voxels. Functional connectivity strength was calculated to explore the brain network hubs. We found that both the TD and PIGD subtypes had comprehensive disrupted regions. These mainly involved the basal ganglia, cerebellum, superior temporal gyrus, pre- and postcentral gyri, inferior frontal gyrus, middle temporal gyrus, lingual gyrus, insula, and parahippocampal gyrus. Furthermore, the PIGD subgroup had more disrupted hubs in the cerebellum than the TD subgroup. These disruptions of hub connectivity were not correlated with the HY stage or disease duration. Our results emphasize the subtype-specific PD-related degeneration of brain hubs, providing novel insights into the pathophysiological mechanisms of connectivity dysfunction in different PD subgroups. © 2017 S. Karger AG, Basel.

  7. Development of human brain structural networks through infancy and childhood.

    Science.gov (United States)

    Huang, Hao; Shu, Ni; Mishra, Virendra; Jeon, Tina; Chalak, Lina; Wang, Zhiyue J; Rollins, Nancy; Gong, Gaolang; Cheng, Hua; Peng, Yun; Dong, Qi; He, Yong

    2015-05-01

    During human brain development through infancy and childhood, microstructural and macrostructural changes take place to reshape the brain's structural networks and better adapt them to sophisticated functional and cognitive requirements. However, structural topological configuration of the human brain during this specific development period is not well understood. In this study, diffusion magnetic resonance image (dMRI) of 25 neonates, 13 toddlers, and 25 preadolescents were acquired to characterize network dynamics at these 3 landmark cross-sectional ages during early childhood. dMRI tractography was used to construct human brain structural networks, and the underlying topological properties were quantified by graph-theory approaches. Modular organization and small-world attributes are evident at birth with several important topological metrics increasing monotonically during development. Most significant increases of regional nodes occur in the posterior cingulate cortex, which plays a pivotal role in the functional default mode network. Positive correlations exist between nodal efficiencies and fractional anisotropy of the white matter traced from these nodes, while correlation slopes vary among the brain regions. These results reveal substantial topological reorganization of human brain structural networks through infancy and childhood, which is likely to be the outcome of both heterogeneous strengthening of the major white matter tracts and pruning of other axonal fibers. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  8. Network attributes underlying intellectual giftedness in the developing brain.

    Science.gov (United States)

    Ma, Jiyoung; Kang, Hee Jin; Kim, Jung Yoon; Jeong, Hyeonseok S; Im, Jooyeon Jamie; Namgung, Eun; Kim, Myeong Ju; Lee, Suji; Kim, Tammy D; Oh, Jin Kyoung; Chung, Yong-An; Lyoo, In Kyoon; Lim, Soo Mee; Yoon, Sujung

    2017-09-12

    Brain network is organized to maximize the efficiency of both segregated and integrated information processing that may be related to human intelligence. However, there have been surprisingly few studies that focus on the topological characteristics of brain network underlying extremely high intelligence that is intellectual giftedness, particularly in adolescents. Here, we examined the network topology in 25 adolescents with superior intelligence (SI-Adol), 25 adolescents with average intelligence (AI-Adol), and 27 young adults with AI (AI-Adult). We found that SI-Adol had network topological properties of high global efficiency as well as high clustering with a low wiring cost, relative to AI-Adol. However, contrary to the suggested role that brain hub regions play in general intelligence, the network efficiency of rich club connection matrix, which represents connections among brain hubs, was low in SI-Adol in comparison to AI-Adol. Rather, a higher level of local connection density was observed in SI-Adol than in AI-Adol. The highly intelligent brain may not follow this efficient yet somewhat stereotypical process of information integration entirely. Taken together, our results suggest that a highly intelligent brain may communicate more extensively, while being less dependent on rich club communications during adolescence.

  9. Complex modular structure of large-scale brain networks

    Science.gov (United States)

    Valencia, M.; Pastor, M. A.; Fernández-Seara, M. A.; Artieda, J.; Martinerie, J.; Chavez, M.

    2009-06-01

    Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large scale (voxel level) extracted from functional magnetic resonance imaging signals. By using a random-walk-based method, we unveil the modularity of brain webs and show modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intramodular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.

  10. THE IMPACT OF POVERTY ON THE DEVELOPMENT OF BRAIN NETWORKS

    Directory of Open Access Journals (Sweden)

    Sebastian J Lipina

    2012-08-01

    Full Text Available Although the study of brain development in non-human animals is an old one, recent imaging methods have allowed non-invasive studies of the grey and white matter of the human brain over the lifespan. Classic animal studies show clearly that impoverished environments reduce cortical grey matter in relation to complex environments and cognitive and imaging studies in humans suggest which networks may be most influenced by poverty. Studies have been clear in showing the plasticity of many brain systems, but whether sensitivity to learning differs over the lifespan and for which networks is still unclear. A major task for current research is a successful integration of these methods to understand how development and learning shape the neural networks underlying achievements in literacy, numeracy, and attention. This paper seeks to foster further integration by reviewing the currents state of knowledge relating brain changes to behavior and indicating possible future directions.

  11. Stimulation-Based Control of Dynamic Brain Networks.

    Directory of Open Access Journals (Sweden)

    Sarah Feldt Muldoon

    2016-09-01

    Full Text Available The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of these focal perturbations. To study the system wide impact of regional stimulation, we employ a data-driven computational model of nonlinear brain dynamics to systematically explore the effects of targeted stimulation. Validating predictions from network control theory, we uncover the relationship between regional controllability and the focal versus global impact of stimulation, and we relate these findings to differences in the underlying network architecture. Finally, by mapping brain regions to cognitive systems, we observe that the default mode system imparts large global change despite being highly constrained by structural connectivity. This work forms an important step towards the development of personalized stimulation protocols for medical treatment or performance enhancement.

  12. Brain networks modulated by subthalamic nucleus deep brain stimulation.

    Science.gov (United States)

    Accolla, Ettore A; Herrojo Ruiz, Maria; Horn, Andreas; Schneider, Gerd-Helge; Schmitz-Hübsch, Tanja; Draganski, Bogdan; Kühn, Andrea A

    2016-09-01

    Deep brain stimulation of the subthalamic nucleus is an established treatment for the motor symptoms of Parkinson's disease. Given the frequent occurrence of stimulation-induced affective and cognitive adverse effects, a better understanding about the role of the subthalamic nucleus in non-motor functions is needed. The main goal of this study is to characterize anatomical circuits modulated by subthalamic deep brain stimulation, and infer about the inner organization of the nucleus in terms of motor and non-motor areas. Given its small size and anatomical intersubject variability, functional organization of the subthalamic nucleus is difficult to investigate in vivo with current methods. Here, we used local field potential recordings obtained from 10 patients with Parkinson's disease to identify a subthalamic area with an analogous electrophysiological signature, namely a predominant beta oscillatory activity. The spatial accuracy was improved by identifying a single contact per macroelectrode for its vicinity to the electrophysiological source of the beta oscillation. We then conducted whole brain probabilistic tractography seeding from the previously identified contacts, and further described connectivity modifications along the macroelectrode's main axis. The designated subthalamic 'beta' area projected predominantly to motor and premotor cortical regions additional to connections to limbic and associative areas. More ventral subthalamic areas showed predominant connectivity to medial temporal regions including amygdala and hippocampus. We interpret our findings as evidence for the convergence of different functional circuits within subthalamic nucleus' portions deemed to be appropriate as deep brain stimulation target to treat motor symptoms in Parkinson's disease. Potential clinical implications of our study are illustrated by an index case where deep brain stimulation of estimated predominant non-motor subthalamic nucleus induced hypomanic behaviour. © The

  13. Dynamic neural network reorganization associated with second language vocabulary acquisition: a multimodal imaging study.

    Science.gov (United States)

    Hosoda, Chihiro; Tanaka, Kanji; Nariai, Tadashi; Honda, Manabu; Hanakawa, Takashi

    2013-08-21

    It remains unsettled whether human language relies exclusively on innately privileged brain structure in the left hemisphere or is more flexibly shaped through experiences, which induce neuroplastic changes in potentially relevant neural circuits. Here we show that learning of second language (L2) vocabulary and its cessation can induce bidirectional changes in the mirror-reverse of the traditional language areas. A cross-sectional study identified that gray matter volume in the inferior frontal gyrus pars opercularis (IFGop) and connectivity of the IFGop with the caudate nucleus and the superior temporal gyrus/supramarginal (STG/SMG), predominantly in the right hemisphere, were positively correlated with L2 vocabulary competence. We then implemented a cohort study involving 16 weeks of L2 training in university students. Brain structure before training did not predict the later gain in L2 ability. However, training intervention did increase IFGop volume and reorganization of white matter including the IFGop-caudate and IFGop-STG/SMG pathways in the right hemisphere. These "positive" plastic changes were correlated with the gain in L2 ability in the trained group but were not observed in the control group. We propose that the right hemispheric network can be reorganized into language-related areas through use-dependent plasticity in young adults, reflecting a repertoire of flexible reorganization of the neural substrates responding to linguistic experiences.

  14. Language and cognition in a bilingual child after traumatic brain injury in infancy: long-term plasticity and vulnerability.

    Science.gov (United States)

    Tavano, Alessandro; Galbiati, Susanna; Recla, Monica; Formica, Francesca; Giordano, Flavio; Genitori, Lorenzo; Strazzer, Sandra

    2009-02-01

    This study aimed at investigating the long-term effects of the combination of severity of injury and time of injury in a 6-year-old bilingual Arabic-Italian child who sustained a severe left traumatic brain injury at the age of 7 months. Standard neurological, cognitive and neuropsychological assessments were administered at 40 days after surgery and again at 18, 31, 62 and 73 months. The child presented with developmental arrest at 18 and 31 months. Later on, right hemiparetic and oculomotor signs gradually improved to a significant extent, as well as dysexecutive, visuospatial and praxic deficits. At present, persistent language disorders in a fluent speech characterize the child's profile to a similar extent and type in both languages, suggesting common underlying learning strategies which are ineffective for procedurally acquiring language. This case confirms that children who sustain severe left hemisphere traumatic brain injury in infancy present with increased vulnerability to linguistic deficits. Left frontotemporal, cortical-subcortical lesions which occur during very early language development may permanently disrupt the procedural language acquisition network required for first language acquisition.

  15. Disruption of structural covariance networks for language in autism is modulated by verbal ability.

    Science.gov (United States)

    Sharda, Megha; Khundrakpam, Budhachandra S; Evans, Alan C; Singh, Nandini C

    2016-03-01

    The presence of widespread speech and language deficits is a core feature of autism spectrum disorders (ASD). These impairments have often been attributed to altered connections between brain regions. Recent developments in anatomical correlation-based approaches to map structural covariance offer an effective way of studying such connections in vivo. In this study, we employed such a structural covariance network (SCN)-based approach to investigate the integrity of anatomical networks in fronto-temporal brain regions of twenty children with ASD compared to an age and gender-matched control group of twenty-two children. Our findings reflected large-scale disruption of inter and intrahemispheric covariance in left frontal SCNs in the ASD group compared to controls, but no differences in right fronto-temporal SCNs. Interhemispheric covariance in left-seeded networks was further found to be modulated by verbal ability of the participants irrespective of autism diagnosis, suggesting that language function might be related to the strength of interhemispheric structural covariance between frontal regions. Additionally, regional cortical thickening was observed in right frontal and left posterior regions, which was predicted by decreasing symptom severity and increasing verbal ability in ASD. These findings unify reports of regional differences in cortical morphology in ASD. They also suggest that reduced left hemisphere asymmetry and increased frontal growth may not only reflect neurodevelopmental aberrations but also compensatory mechanisms.

  16. Toward the Language-Ready Brain: Biological Evolution and Primate Comparisons.

    Science.gov (United States)

    Arbib, Michael A

    2017-02-01

    The approach to language evolution suggested here focuses on three questions: How did the human brain evolve so that humans can develop, use, and acquire languages? How can the evolutionary quest be informed by studying brain, behavior, and social interaction in monkeys, apes, and humans? How can computational modeling advance these studies? I hypothesize that the brain is language ready in that the earliest humans had protolanguages but not languages (i.e., communication systems endowed with rich and open-ended lexicons and grammars supporting a compositional semantics), and that it took cultural evolution to yield societies (a cultural constructed niche) in which language-ready brains could become language-using brains. The mirror system hypothesis is a well-developed example of this approach, but I offer it here not as a closed theory but as an evolving framework for the development and analysis of conflicting subhypotheses in the hope of their eventual integration. I also stress that computational modeling helps us understand the evolving role of mirror neurons, not in and of themselves, but only in their interaction with systems "beyond the mirror." Because a theory of evolution needs a clear characterization of what it is that evolved, I also outline ideas for research in neurolinguistics to complement studies of the evolution of the language-ready brain. A clear challenge is to go beyond models of speech comprehension to include sign language and models of production, and to link language to visuomotor interaction with the physical and social world.

  17. The Virtual Brain: a simulator of primate brain network dynamics

    Directory of Open Access Journals (Sweden)

    Paula eSanz Leon

    2013-06-01

    Full Text Available We present TheVirtualBrain (TVB, a neuroinformatics platform for full brainnetwork simulations using biologically realistic connectivity. This simulationenvironment enables the model-based inference of neurophysiological mechanismsacross different brain scales that underlie the generation of macroscopicneuroimaging signals including functional MRI (fMRI, EEG and MEG. Researchersfrom different backgrounds can benefit from an integrative software platformincluding a supporting framework for data management (generation,organization, storage, integration and sharing and a simulation core writtenin Python. TVB allows the reproduction and evaluation of personalizedconfigurations of the brain by using individual subject data. Thispersonalization facilitates an exploration of the consequences of pathologicalchanges in the system, permitting to investigate potential ways to counteractsuch unfavorable processes. The architecture of TVB supports interaction withMATLAB packages, for example, the well known Brain Connectivity Toolbox. TVBcan be used in a client-server configuration, such that it can be remotelyaccessed through the Internet thanks to its web-basedHTML5, JS and WebGL graphical user interface. TVB is alsoaccessible as a standalone cross-platform Python library and application, andusers can interact with the scientific core through the scripting interfaceIDLE, enabling easy modeling, development and debugging of the scientifickernel. This second interface makes TVB extensible by combining it with otherlibraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to thedevelopment of TVB, the architecture and features of its major softwarecomponents as well as potential neuroscience applications.

  18. Semantics for Hybrid Networks Using the Network Description Language

    NARCIS (Netherlands)

    Ham, J.J. van der; Grosso, P.; Dijkstra, F.; Laat, C. de

    2006-01-01

    Hybrid networks offer end users a mix of traditional connections and new optical services in the form of dedicated lightpaths. These must be requested in advance and are currently configured on demand by the operators. Because lightpaths are circuit switched, the user must be aware of the topology

  19. Mapping Multiplex Hubs in Human Functional Brain Networks.

    Science.gov (United States)

    De Domenico, Manlio; Sasai, Shuntaro; Arenas, Alex

    2016-01-01

    Typical brain networks consist of many peripheral regions and a few highly central ones, i.e., hubs, playing key functional roles in cerebral inter-regional interactions. Studies have shown that networks, obtained from the analysis of specific frequency components of brain activity, present peculiar architectures with unique profiles of region centrality. However, the identification of hubs in networks built from different frequency bands simultaneously is still a challenging problem, remaining largely unexplored. Here we identify each frequency component with one layer of a multiplex network and face this challenge by exploiting the recent advances in the analysis of multiplex topologies. First, we show that each frequency band carries unique topological information, fundamental to accurately model brain functional networks. We then demonstrate that hubs in the multiplex network, in general different from those ones obtained after discarding or aggregating the measured signals as usual, provide a more accurate map of brain's most important functional regions, allowing to distinguish between healthy and schizophrenic populations better than conventional network approaches.

  20. Beyond localized and distributed accounts of brain functions. Comment on “Understanding brain networks and brain organization” by Pessoa

    Science.gov (United States)

    Cauda, Franco; Costa, Tommaso; Tamietto, Marco

    2014-09-01

    Recent evidence in cognitive neuroscience lends support to the idea that network models of brain architecture provide a privileged access to the understanding of the relation between brain organization and cognitive processes [1]. The core perspective holds that cognitive processes depend on the interactions among distributed neuronal populations and brain structures, and that the impact of a given region on behavior largely depends on its pattern of anatomical and functional connectivity [2,3].

  1. BrainNet Viewer: a network visualization tool for human brain connectomics.

    Science.gov (United States)

    Xia, Mingrui; Wang, Jinhui; He, Yong

    2013-01-01

    The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).

  2. BrainNet Viewer: a network visualization tool for human brain connectomics.

    Directory of Open Access Journals (Sweden)

    Mingrui Xia

    Full Text Available The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI, we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/.

  3. The maturing architecture of the brain's default network.

    Science.gov (United States)

    Fair, Damien A; Cohen, Alexander L; Dosenbach, Nico U F; Church, Jessica A; Miezin, Francis M; Barch, Deanna M; Raichle, Marcus E; Petersen, Steven E; Schlaggar, Bradley L

    2008-03-11

    In recent years, the brain's "default network," a set of regions characterized by decreased neural activity during goal-oriented tasks, has generated a significant amount of interest, as well as controversy. Much of the discussion has focused on the relationship of these regions to a "default mode" of brain function. In early studies, investigators suggested that, the brain's default mode supports "self-referential" or "introspective" mental activity. Subsequently, regions of the default network have been more specifically related to the "internal narrative," the "autobiographical self," "stimulus independent thought," "mentalizing," and most recently "self-projection." However, the extant literature on the function of the default network is limited to adults, i.e., after the system has reached maturity. We hypothesized that further insight into the network's functioning could be achieved by characterizing its development. In the current study, we used resting-state functional connectivity MRI (rs-fcMRI) to characterize the development of the brain's default network. We found that the default regions are only sparsely functionally connected at early school age (7-9 years old); over development, these regions integrate into a cohesive, interconnected network.

  4. The timing of language learning shapes brain structure associated with articulation.

    Science.gov (United States)

    Berken, Jonathan A; Gracco, Vincent L; Chen, Jen-Kai; Klein, Denise

    2016-09-01

    We compared the brain structure of highly proficient simultaneous (two languages from birth) and sequential (second language after age 5) bilinguals, who differed only in their degree of native-like accent, to determine how the brain develops when a skill is acquired from birth versus later in life. For the simultaneous bilinguals, gray matter density was increased in the left putamen, as well as in the left posterior insula, right dorsolateral prefrontal cortex, and left and right occipital cortex. For the sequential bilinguals, gray matter density was increased in the bilateral premotor cortex. Sequential bilinguals with better accents also showed greater gray matter density in the left putamen, and in several additional brain regions important for sensorimotor integration and speech-motor control. Our findings suggest that second language learning results in enhanced brain structure of specific brain areas, which depends on whether two languages are learned simultaneously or sequentially, and on the extent to which native-like proficiency is acquired.

  5. Brain networks underlying mental imagery of auditory and visual information.

    Science.gov (United States)

    Zvyagintsev, Mikhail; Clemens, Benjamin; Chechko, Natalya; Mathiak, Krystyna A; Sack, Alexander T; Mathiak, Klaus

    2013-05-01

    Mental imagery is a complex cognitive process that resembles the experience of perceiving an object when this object is not physically present to the senses. It has been shown that, depending on the sensory nature of the object, mental imagery also involves correspondent sensory neural mechanisms. However, it remains unclear which areas of the brain subserve supramodal imagery processes that are independent of the object modality, and which brain areas are involved in modality-specific imagery processes. Here, we conducted a functional magnetic resonance imaging study to reveal supramodal and modality-specific networks of mental imagery for auditory and visual information. A common supramodal brain network independent of imagery modality, two separate modality-specific networks for imagery of auditory and visual information, and a common deactivation network were identified. The supramodal network included brain areas related to attention, memory retrieval, motor preparation and semantic processing, as well as areas considered to be part of the default-mode network and multisensory integration areas. The modality-specific networks comprised brain areas involved in processing of respective modality-specific sensory information. Interestingly, we found that imagery of auditory information led to a relative deactivation within the modality-specific areas for visual imagery, and vice versa. In addition, mental imagery of both auditory and visual information widely suppressed the activity of primary sensory and motor areas, for example deactivation network. These findings have important implications for understanding the mechanisms that are involved in generation of mental imagery. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  6. The social brain is not enough: on the importance of the ecological brain for the origin of language

    Directory of Open Access Journals (Sweden)

    Francesco Ferretti

    2016-08-01

    Full Text Available In this paper, I assume that the study of the origin of language is strictly connected to the analysis of the traits that distinguish human language from animal communication. Usually, human language is said to be unique in the animal kingdom because it enables and/or requires intentionality or mindreading. By emphasizing the importance of mindreading, the social brain hypothesis has provided major insights within the origin of language debate. However, as studies on non-human primates have demonstrated that intentional forms of communication are already present in these species to a greater or lesser extent, I maintain that the social brain is a necessary but not a sufficient condition to explain the uniqueness of language. In this paper, I suggest that the distinctive feature of human communication resides in the ability to tell stories, and that the origin of language should be traced with respect to the capacity to produce discourses, rather than phrases or words. As narrative requires the ability to link events distant from one another in space and time, my proposal is that in order to explain the origin of language, we need to appeal to both the social brain and the ecological brain – that is, the cognitive devices which allow us to mentally travel in space and time.

  7. The Social Brain Is Not Enough: On the Importance of the Ecological Brain for the Origin of Language.

    Science.gov (United States)

    Ferretti, Francesco

    2016-01-01

    In this paper, I assume that the study of the origin of language is strictly connected to the analysis of the traits that distinguish human language from animal communication. Usually, human language is said to be unique in the animal kingdom because it enables and/or requires intentionality or mindreading. By emphasizing the importance of mindreading, the social brain hypothesis has provided major insights within the origin of language debate. However, as studies on non-human primates have demonstrated that intentional forms of communication are already present in these species to a greater or lesser extent, I maintain that the social brain is a necessary but not a sufficient condition to explain the uniqueness of language. In this paper, I suggest that the distinctive feature of human communication resides in the ability to tell stories, and that the origin of language should be traced with respect to the capacity to produce discourses, rather than phrases or words. As narrative requires the ability to link events distant from one another in space and time, my proposal is that in order to explain the origin of language, we need to appeal to both the social brain and the ecological brain - that is, the cognitive devices which allow us to mentally travel in space and time.

  8. Language disorders and their meanings: the effects of a speech-language pathology network activity

    Directory of Open Access Journals (Sweden)

    Rosana Carla do Nascimento Givigi

    2015-03-01

    Full Text Available This study follows the epistemological assumptions of the Brazilian Interactionism, articulated with the Discourse Analysis and Meaning Network. The main purpose was to analyze the effects of the intervention work with children, their families and schools. The intervention aimed at the construction of language and the modification of the meanings attached to these subjects. The methodological device used clinical-qualitative and action research. Five children with language disorders aged 0 to 5 years, their families and schools participated in this two-year study. The procedures were distinct for the different networks: child, family, school. The speech therapy sessions were performed weekly and were based on the Interactionist approach. Interviews with the families were conducted, as well as meetings with the group of parents. At school, the weekly visits used the collaborative action research perspective. The main results were modifications in the children’s behaviour; modification of the meanings given to language disorders; more communicative attempts; more efficient interactions; and collaborative work in schools. The idea of human development based on a historical and cultural process of significations was the guideline of the study. It was possible to verify that, after the network activity, there was a gradual modification of the meanings of language disorders in parents, educational agents and children. Actual life conditions and discursive practices are interwoven throughout time, enabling to reflect on the dynamics of relationships and developing processes.

  9. Neural murmurations. Comment on “Understanding brain networks and brain organization” by Luiz Pessoa

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    Laurienti, Paul J.

    2014-09-01

    If not the last frontier, understanding the human brain is certainly one of the last. Over the past decade there has been a shift in the focus of neuroscience. The concept of the brain as a network is gaining traction and is rapidly becoming a dominant perspective [1]. In the target article [2], Luiz Pessoa discusses major conceptual shifts that must accompany the methodological changes associated with network science applications to the brain. The software, algorithms, and computational power needed to perform network analyses are now at the fingertips of all neuroscientists. But, this places us at a fork in the road. Will these tools be used to substantiate what has already been discovered, or will we seek a totally new and improved understanding of the brain?

  10. Imaging network level language recovery after left PCA stroke.

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    Sebastian, Rajani; Long, Charltien; Purcell, Jeremy J; Faria, Andreia V; Lindquist, Martin; Jarso, Samson; Race, David; Davis, Cameron; Posner, Joseph; Wright, Amy; Hillis, Argye E

    2016-05-11

    The neural mechanisms that support aphasia recovery are not yet fully understood. Our goal was to evaluate longitudinal changes in naming recovery in participants with posterior cerebral artery (PCA) stroke using a case-by-case analysis. Using task based and resting state functional magnetic resonance imaging (fMRI) and detailed language testing, we longitudinally studied the recovery of the naming network in four participants with PCA stroke with naming deficits at the acute (0 week), sub acute (3-5 weeks), and chronic time point (5-7 months) post stroke. Behavioral and imaging analyses (task related and resting state functional connectivity) were carried out to elucidate longitudinal changes in naming recovery. Behavioral and imaging analysis revealed that an improvement in naming accuracy from the acute to the chronic stage was reflected by increased connectivity within and between left and right hemisphere "language" regions. One participant who had persistent moderate naming deficit showed weak and decreasing connectivity longitudinally within and between left and right hemisphere language regions. These findings emphasize a network view of aphasia recovery, and show that the degree of inter- and intra- hemispheric balance between the language-specific regions is necessary for optimal recovery of naming, at least in participants with PCA stroke.

  11. Development of the Intrinsic Language Network in Preschool Children from Ages 3 to 5 Years.

    Directory of Open Access Journals (Sweden)

    Yaqiong Xiao

    Full Text Available Resting state studies of spontaneous fluctuations in the functional magnetic resonance imaging (fMRI blood oxygen level dependent signal have shown great potential in mapping the intrinsic functional connectivity of the human brain underlying cognitive functions. The aim of the present study was to explore the developmental changes in functional networks of the developing human brain exemplified with the language network in typically developing preschool children. To this end, resting-sate fMRI data were obtained from native Chinese children at ages of 3 and 5 years, 15 in each age group. Resting-state functional connectivity (RSFC was analyzed for four regions of interest; these are the left and right anterior superior temporal gyrus (aSTG, left posterior superior temporal gyrus (pSTG, and left inferior frontal gyrus (IFG. The comparison of these RSFC maps between 3- and 5-year-olds revealed that RSFC decreases in the right aSTG and increases in the left hemisphere between aSTG seed and IFG, between pSTG seed and IFG, as well as between IFG seed and posterior superior temporal sulcus. In a subsequent analysis, functional asymmetry of the language network seeding in aSTG, pSTG and IFG was further investigated. The results showed an increase of left lateralization in both RSFC of pSTG and of IFG from ages 3 to 5 years. The IFG showed a leftward lateralized trend in 3-year-olds, while pSTG demonstrated rightward asymmetry in 5-year-olds. These findings suggest clear developmental trajectories of the language network between 3- and 5-year-olds revealed as a function of age, characterized by increasing long-range connections and dynamic hemispheric lateralization with age. Our study provides new insights into the developmental changes of a well-established functional network in young children and also offers a basis for future cross-culture and cross-age studies of the resting-state language network.

  12. Development of the Intrinsic Language Network in Preschool Children from Ages 3 to 5 Years.

    Science.gov (United States)

    Xiao, Yaqiong; Brauer, Jens; Lauckner, Mark; Zhai, Hongchang; Jia, Fucang; Margulies, Daniel S; Friederici, Angela D

    2016-01-01

    Resting state studies of spontaneous fluctuations in the functional magnetic resonance imaging (fMRI) blood oxygen level dependent signal have shown great potential in mapping the intrinsic functional connectivity of the human brain underlying cognitive functions. The aim of the present study was to explore the developmental changes in functional networks of the developing human brain exemplified with the language network in typically developing preschool children. To this end, resting-sate fMRI data were obtained from native Chinese children at ages of 3 and 5 years, 15 in each age group. Resting-state functional connectivity (RSFC) was analyzed for four regions of interest; these are the left and right anterior superior temporal gyrus (aSTG), left posterior superior temporal gyrus (pSTG), and left inferior frontal gyrus (IFG). The comparison of these RSFC maps between 3- and 5-year-olds revealed that RSFC decreases in the right aSTG and increases in the left hemisphere between aSTG seed and IFG, between pSTG seed and IFG, as well as between IFG seed and posterior superior temporal sulcus. In a subsequent analysis, functional asymmetry of the language network seeding in aSTG, pSTG and IFG was further investigated. The results showed an increase of left lateralization in both RSFC of pSTG and of IFG from ages 3 to 5 years. The IFG showed a leftward lateralized trend in 3-year-olds, while pSTG demonstrated rightward asymmetry in 5-year-olds. These findings suggest clear developmental trajectories of the language network between 3- and 5-year-olds revealed as a function of age, characterized by increasing long-range connections and dynamic hemispheric lateralization with age. Our study provides new insights into the developmental changes of a well-established functional network in young children and also offers a basis for future cross-culture and cross-age studies of the resting-state language network.

  13. Coexpression networks identify brain region-specific enhancer RNAs in the human brain.

    Science.gov (United States)

    Yao, Pu; Lin, Peijie; Gokoolparsadh, Akira; Assareh, Amelia; Thang, Mike W C; Voineagu, Irina

    2015-08-01

    Despite major progress in identifying enhancer regions on a genome-wide scale, the majority of available data are limited to model organisms and human transformed cell lines. We have identified a robust set of enhancer RNAs (eRNAs) expressed in the human brain and constructed networks assessing eRNA-gene coexpression interactions across human fetal brain and multiple adult brain regions. Our data identify brain region-specific eRNAs and show that enhancer regions expressing eRNAs are enriched for genetic variants associated with autism spectrum disorders.

  14. Social Networking Sites (SNSs- Shifting Paradigm of English Language Usage

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    Hetal K. Kachhia

    2014-06-01

    Full Text Available English is the globally accepted language in various nations and professions in different varieties, but the English that has acquired a wider spectrum than all these Englishes is the English used in Social Networking Sites which has changed the scenario of English language usage due to the ease in its accessibility and the kind of flexibility of language usage. The English used in Social Networking Sites like Facebook and Twitter has changed the linguistic behaviour of the people by producing a number of acronyms like BFF, FB etc, creating new verb forms like ‘to tweet’ or nouns like ‘tweeple’ or producing many compound nouns such as ‘netiquette’, changing the meaning of traditional verbs and nouns by introducing new meanings to them, e.g. the word ‘friend’ is used to refer “someone to an online list of acquaintances”, and by making use of prefixes like ‘un’ for the purpose of conveying the meaning of negation as in ‘unlike a comment/update’ by ignoring its original prefix ‘dis’ for referring the antonym of ‘like’. By emphasizing on the aim of communication, grammar and vocabulary are put on the peripheral value in Social Networking Sites. Therefore, the focal point of this paper is to study the changes in the linguistic behaviour of the people caused by the SNSs.

  15. Differential brain network activity across mood states in bipolar disorder.

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    Brady, Roscoe O; Tandon, Neeraj; Masters, Grace A; Margolis, Allison; Cohen, Bruce M; Keshavan, Matcheri; Öngür, Dost

    2017-01-01

    This study aimed to identify how the activity of large-scale brain networks differs between mood states in bipolar disorder. The authors measured spontaneous brain activity in subjects with bipolar disorder in mania and euthymia and compared these states to a healthy comparison population. 23 subjects with bipolar disorder type I in a manic episode, 24 euthymic bipolar I subjects, and 23 matched healthy comparison (HC) subjects underwent resting state fMRI scans. Using an existing parcellation of the whole brain, we measured functional connectivity between brain regions and identified significant differences between groups. In unbiased whole-brain analyses, functional connectivity between parietal, occipital, and frontal nodes within the dorsal attention network (DAN) were significantly greater in mania than euthymia or HC subjects. In the default mode network (DMN), connectivity between dorsal frontal nodes and the rest of the DMN differentiated both mood state and diagnosis. The bipolar groups were separate cohorts rather than subjects imaged longitudinally across mood states. Bipolar mood states are associated with highly significant alterations in connectivity in two large-scale brain networks. These same networks also differentiate bipolar mania and euthymia from a HC population. State related changes in DAN and DMN connectivity suggest a circuit based pathology underlying cognitive dysfunction as well as activity/reactivity in bipolar mania. Altered activities in neural networks may be biomarkers of bipolar disorder diagnosis and mood state that are accessible to neuromodulation and are promising novel targets for scientific investigation and possible clinical intervention. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Small-world human brain networks: Perspectives and challenges.

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    Liao, Xuhong; Vasilakos, Athanasios V; He, Yong

    2017-06-01

    Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Electrophysiological signatures of atypical intrinsic brain connectivity networks in autism

    Science.gov (United States)

    Shou, Guofa; Mosconi, Matthew W.; Wang, Jun; Ethridge, Lauren E.; Sweeney, John A.; Ding, Lei

    2017-08-01

    Objective. Abnormal local and long-range brain connectivity have been widely reported in autism spectrum disorder (ASD), yet the nature of these abnormalities and their functional relevance at distinct cortical rhythms remains unknown. Investigations of intrinsic connectivity networks (ICNs) and their coherence across whole brain networks hold promise for determining whether patterns of functional connectivity abnormalities vary across frequencies and networks in ASD. In the present study, we aimed to probe atypical intrinsic brain connectivity networks in ASD from resting-state electroencephalography (EEG) data via characterizing the whole brain network. Approach. Connectivity within individual ICNs (measured by spectral power) and between ICNs (measured by coherence) were examined at four canonical frequency bands via a time-frequency independent component analysis on high-density EEG, which were recorded from 20 ASD and 20 typical developing (TD) subjects during an eyes-closed resting state. Main results. Among twelve identified electrophysiological ICNs, individuals with ASD showed hyper-connectivity in individual ICNs and hypo-connectivity between ICNs. Functional connectivity alterations in ASD were more severe in the frontal lobe and the default mode network (DMN) and at low frequency bands. These functional connectivity measures also showed abnormal age-related associations in ICNs related to frontal, temporal and motor regions in ASD. Significance. Our findings suggest that ASD is characterized by the opposite directions of abnormalities (i.e. hypo- and hyper-connectivity) in the hierarchical structure of the whole brain network, with more impairments in the frontal lobe and the DMN at low frequency bands, which are critical for top-down control of sensory systems, as well as for both cognition and social skills.

  18. Hierarchical multi-resolution mesh networks for brain decoding.

    Science.gov (United States)

    Onal Ertugrul, Itir; Ozay, Mete; Yarman Vural, Fatos T

    2017-10-04

    Human brain is supposed to process information in multiple frequency bands. Therefore, we can extract diverse information from functional Magnetic Resonance Imaging (fMRI) data by processing it at multiple resolutions. We propose a framework, called Hierarchical Multi-resolution Mesh Networks (HMMNs), which establishes a set of brain networks at multiple resolutions of fMRI signal to represent the underlying cognitive process. Our framework, first, decomposes the fMRI signal into various frequency subbands using wavelet transform. Then, a brain network is formed at each subband by ensembling a set of local meshes. Arc weights of each local mesh are estimated by ridge regression. Finally, adjacency matrices of mesh networks obtained at different subbands are used to train classifiers in an ensemble learning architecture, called fuzzy stacked generalization (FSG). Our decoding performances on Human Connectome Project task-fMRI dataset reflect that HMMNs can successfully discriminate tasks with 99% accuracy, across 808 subjects. Diversity of information embedded in mesh networks of multiple subbands enables the ensemble of classifiers to collaborate with each other for brain decoding. The suggested HMMNs decode the cognitive tasks better than a single classifier applied to any subband. Also mesh networks have a better representation power compared to pairwise correlations or average voxel time series. Moreover, fusion of diverse information using FSG outperforms fusion with majority voting. We conclude that, fMRI data, recorded during a cognitive task, provide diverse information in multi-resolution mesh networks. Our framework fuses this complementary information and boosts the brain decoding performances obtained at individual subbands.

  19. Neural networks underlying language and social cognition during self-other processing in Autism spectrum disorders.

    Science.gov (United States)

    Kana, Rajesh K; Sartin, Emma B; Stevens, Carl; Deshpande, Hrishikesh D; Klein, Christopher; Klinger, Mark R; Klinger, Laura Grofer

    2017-07-28

    The social communication impairments defining autism spectrum disorders (ASD) may be built upon core deficits in perspective-taking, language processing, and self-other representation. Self-referential processing entails the ability to incorporate self-awareness, self-judgment, and self-memory in information processing. Very few studies have examined the neural bases of integrating self-other representation and semantic processing in individuals with ASD. The main objective of this functional MRI study is to examine the role of language and social brain networks in self-other processing in young adults with ASD. Nineteen high-functioning male adults with ASD and 19 age-sex-and-IQ-matched typically developing (TD) control participants made "yes" or "no" judgments of whether an adjective, presented visually, described them (self) or their favorite teacher (other). Both ASD and TD participants showed significantly increased activity in the medial prefrontal cortex (MPFC) during self and other processing relative to letter search. Analyses of group differences revealed significantly reduced activity in left inferior frontal gyrus (LIFG), and left inferior parietal lobule (LIPL) in ASD participants, relative to TD controls. ASD participants also showed significantly weaker functional connectivity of the anterior cingulate cortex (ACC) with several brain areas while processing self-related words. The LIFG and IPL are important regions functionally at the intersection of language and social roles; reduced recruitment of these regions in ASD participants may suggest poor level of semantic and social processing. In addition, poor connectivity of the ACC may suggest the difficulty in meeting the linguistic and social demands of this task in ASD. Overall, this study provides new evidence of the altered recruitment of the neural networks underlying language and social cognition in ASD. Published by Elsevier Ltd.

  20. Riemannian multi-manifold modeling and clustering in brain networks

    Science.gov (United States)

    Slavakis, Konstantinos; Salsabilian, Shiva; Wack, David S.; Muldoon, Sarah F.; Baidoo-Williams, Henry E.; Vettel, Jean M.; Cieslak, Matthew; Grafton, Scott T.

    2017-08-01

    This paper introduces Riemannian multi-manifold modeling in the context of brain-network analytics: Brainnetwork time-series yield features which are modeled as points lying in or close to a union of a finite number of submanifolds within a known Riemannian manifold. Distinguishing disparate time series amounts thus to clustering multiple Riemannian submanifolds. To this end, two feature-generation schemes for brain-network time series are put forth. The first one is motivated by Granger-causality arguments and uses an auto-regressive moving average model to map low-rank linear vector subspaces, spanned by column vectors of appropriately defined observability matrices, to points into the Grassmann manifold. The second one utilizes (non-linear) dependencies among network nodes by introducing kernel-based partial correlations to generate points in the manifold of positivedefinite matrices. Based on recently developed research on clustering Riemannian submanifolds, an algorithm is provided for distinguishing time series based on their Riemannian-geometry properties. Numerical tests on time series, synthetically generated from real brain-network structural connectivity matrices, reveal that the proposed scheme outperforms classical and state-of-the-art techniques in clustering brain-network states/structures.

  1. Cell diversity and network dynamics in photosensitive human brain organoids.

    Science.gov (United States)

    Quadrato, Giorgia; Nguyen, Tuan; Macosko, Evan Z; Sherwood, John L; Min Yang, Sung; Berger, Daniel R; Maria, Natalie; Scholvin, Jorg; Goldman, Melissa; Kinney, Justin P; Boyden, Edward S; Lichtman, Jeff W; Williams, Ziv M; McCarroll, Steven A; Arlotta, Paola

    2017-05-04

    In vitro models of the developing brain such as three-dimensional brain organoids offer an unprecedented opportunity to study aspects of human brain development and disease. However, the cells generated within organoids and the extent to which they recapitulate the regional complexity, cellular diversity and circuit functionality of the brain remain undefined. Here we analyse gene expression in over 80,000 individual cells isolated from 31 human brain organoids. We find that organoids can generate a broad diversity of cells, which are related to endogenous classes, including cells from the cerebral cortex and the retina. Organoids could be developed over extended periods (more than 9 months), allowing for the establishment of relatively mature features, including the formation of dendritic spines and spontaneously active neuronal networks. Finally, neuronal activity within organoids could be controlled using light stimulation of photosensitive cells, which may offer a way to probe the functionality of human neuronal circuits using physiological sensory stimuli.

  2. Validation of network communicability metrics for the analysis of brain structural networks.

    Directory of Open Access Journals (Sweden)

    Jennifer Andreotti

    Full Text Available Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

  3. Common and distinct brain networks underlying verbal and visual creativity.

    Science.gov (United States)

    Zhu, Wenfeng; Chen, Qunlin; Xia, Lingxiang; Beaty, Roger E; Yang, Wenjing; Tian, Fang; Sun, Jiangzhou; Cao, Guikang; Zhang, Qinglin; Chen, Xu; Qiu, Jiang

    2017-04-01

    Creativity is imperative to the progression of human civilization, prosperity, and well-being. Past creative researches tends to emphasize the default mode network (DMN) or the frontoparietal network (FPN) somewhat exclusively. However, little is known about how these networks interact to contribute to creativity and whether common or distinct brain networks are responsible for visual and verbal creativity. Here, we use functional connectivity analysis of resting-state functional magnetic resonance imaging data to investigate visual and verbal creativity-related regions and networks in 282 healthy subjects. We found that functional connectivity within the bilateral superior parietal cortex of the FPN was negatively associated with visual and verbal creativity. The strength of connectivity between the DMN and FPN was positively related to both creative domains. Visual creativity was negatively correlated with functional connectivity within the precuneus of the pDMN and right middle frontal gyrus of the FPN, and verbal creativity was negatively correlated with functional connectivity within the medial prefrontal cortex of the aDMN. Critically, the FPN mediated the relationship between the aDMN and verbal creativity, and it also mediated the relationship between the pDMN and visual creativity. Taken together, decreased within-network connectivity of the FPN and DMN may allow for flexible between-network coupling in the highly creative brain. These findings provide indirect evidence for the cooperative role of the default and executive control networks in creativity, extending past research by revealing common and distinct brain systems underlying verbal and visual creative cognition. Hum Brain Mapp 38:2094-2111, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  4. Resting state brain networks in the prairie vole.

    Science.gov (United States)

    Ortiz, Juan J; Portillo, Wendy; Paredes, Raul G; Young, Larry J; Alcauter, Sarael

    2018-01-19

    Resting state functional magnetic resonance imaging (rsfMRI) has shown the hierarchical organization of the human brain into large-scale complex networks, referred as resting state networks. This technique has turned into a promising translational research tool after the finding of similar resting state networks in non-human primates, rodents and other animal models of great value for neuroscience. Here, we demonstrate and characterize the presence of resting states networks in Microtus ochrogaster, the prairie vole, an extraordinary animal model to study complex human-like social behavior, with potential implications for the research of normal social development, addiction and neuropsychiatric disorders. Independent component analysis of rsfMRI data from isoflurane-anestethized prairie voles resulted in cortical and subcortical networks, including primary motor and sensory networks, but also included putative salience and default mode networks. We further discuss how future research could help to close the gap between the properties of the large scale functional organization and the underlying neurobiology of several aspects of social cognition. These results contribute to the evidence of preserved resting state brain networks across species and provide the foundations to explore the use of rsfMRI in the prairie vole for basic and translational research.

  5. Structural brain changes linked to delayed first language acquisition in congenitally deaf individuals.

    Science.gov (United States)

    Pénicaud, Sidonie; Klein, Denise; Zatorre, Robert J; Chen, Jen-Kai; Witcher, Pamela; Hyde, Krista; Mayberry, Rachel I

    2013-02-01

    Early language experience is essential for the development of a high level of linguistic proficiency in adulthood and in a recent functional Magnetic Resonance Imaging (fMRI) experiment, we showed that a delayed acquisition of a first language results in changes in the functional organization of the adult brain (Mayberry et al., 2011). The present study extends the question to explore if delayed acquisition of a first language also modulates the structural development of the brain. To this end, we carried out anatomical MRI in the same group of congenitally deaf individuals who varied in the age of acquisition of a first language, American Sign Language -ASL (Mayberry et al., 2011) and used a neuroanatomical technique, Voxel-Based Morphometry (VBM), to explore changes in gray and white matter concentrations across the brain related to the age of first language acquisition. The results show that delayed acquisition of a first language is associated with changes in tissue concentration in the occipital cortex close to the area that has been found to show functional recruitment during language processing in these deaf individuals with a late age of acquisition. These findings suggest that a lack of early language experience affects not only the functional but also the anatomical organization of the brain. Copyright © 2012 Elsevier Inc. All rights reserved.

  6. Movement priming of EEG/MEG brain responses for action-words characterizes the link between language and action.

    Science.gov (United States)

    Mollo, Giovanna; Pulvermüller, Friedemann; Hauk, Olaf

    2016-01-01

    Activation in sensorimotor areas of the brain following perception of linguistic stimuli referring to objects and actions has been interpreted as evidence for strong theories of embodied semantics. Although a large number of studies have demonstrated this "language-to-action" link, important questions about how activation in the sensorimotor system affects language performance ("action-to-language" link) are yet unanswered. As several authors have recently pointed out, the debate should move away from an "embodied or not" focus, and rather aim to characterize the functional contributions of sensorimotor systems to language processing in more detail. For this purpose, we here introduce a novel movement priming paradigm in combination with electro- and magnetoencephalography (EEG/MEG), which allows investigating effects of motor cortex pre-activation on the spatio-temporal dynamics of action-word evoked brain activation. Participants initiated experimental trials by either finger- or foot-movements before executing a two alternative forced choice task employing action-words. We found differential brain activation during the early stages of subsequent hand- and leg-related word processing, respectively, albeit in the absence of behavioral effects. Distributed source estimation based on combined EEG/MEG measurements revealed that congruency effects between effector type used for response initiation (hand or foot) and action-word category (hand- or foot-related) occurred not only in motor cortex, but also in a classical language comprehension area, posterior superior temporal cortex, already 150 msec after the visual presentation of the word stimulus. This suggests that pre-activation of hand- and leg-motor networks may differentially facilitate the ignition of semantic cell assemblies for hand- and leg-related words, respectively. Our results demonstrate the usefulness of movement priming in combination with neuroimaging to functionally characterize the link between

  7. Foundational perspectives on causality in large-scale brain networks

    Science.gov (United States)

    Mannino, Michael; Bressler, Steven L.

    2015-12-01

    A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

  8. Spoken language interface for a network management system

    Science.gov (United States)

    Remington, Robert J.

    1999-11-01

    Leaders within the Information Technology (IT) industry are expressing a general concern that the products used to deliver and manage today's communications network capabilities require far too much effort to learn and to use, even by highly skilled and increasingly scarce support personnel. The usability of network management systems must be significantly improved if they are to deliver the performance and quality of service needed to meet the ever-increasing demand for new Internet-based information and services. Fortunately, recent advances in spoken language (SL) interface technologies show promise for significantly improving the usability of most interactive IT applications, including network management systems. The emerging SL interfaces will allow users to communicate with IT applications through words and phases -- our most familiar form of everyday communication. Recent advancements in SL technologies have resulted in new commercial products that are being operationally deployed at an increasing rate. The present paper describes a project aimed at the application of new SL interface technology for improving the usability of an advanced network management system. It describes several SL interface features that are being incorporated within an existing system with a modern graphical user interface (GUI), including 3-D visualization of network topology and network performance data. The rationale for using these SL interface features to augment existing user interfaces is presented, along with selected task scenarios to provide insight into how a SL interface will simplify the operator's task and enhance overall system usability.

  9. Language Adjustment of International Students in the US: A Social Network Analysis on the Effects of Language Resources, Language Norm and Technology

    Science.gov (United States)

    Qiu, Wei

    2011-01-01

    The study explores factors that enhance or inhibit the language adjustment of international students in the U.S. Using social network influence model, the study examines the effects of language resources, language norm, and technology use on international students' self-confidence in overall English skills and four subskills, namely, listening,…

  10. Neural networks involved in learning lexical-semantic and syntactic information in a second language.

    Science.gov (United States)

    Mueller, Jutta L; Rueschemeyer, Shirley-Ann; Ono, Kentaro; Sugiura, Motoaki; Sadato, Norihiro; Nakamura, Akinori

    2014-01-01

    The present study used functional magnetic resonance imaging (fMRI) to investigate the neural correlates of language acquisition in a realistic learning environment. Japanese native speakers were trained in a miniature version of German prior to fMRI scanning. During scanning they listened to (1) familiar sentences, (2) sentences including a novel sentence structure, and (3) sentences containing a novel word while visual context provided referential information. Learning-related decreases of brain activation over time were found in a mainly left-hemispheric network comprising classical frontal and temporal language areas as well as parietal and subcortical regions and were largely overlapping for novel words and the novel sentence structure in initial stages of learning. Differences occurred at later stages of learning during which content-specific activation patterns in prefrontal, parietal and temporal cortices emerged. The results are taken as evidence for a domain-general network supporting the initial stages of language learning which dynamically adapts as learners become proficient.

  11. A network of networks model to study phase synchronization using structural connection matrix of human brain

    Science.gov (United States)

    Ferrari, F. A. S.; Viana, R. L.; Reis, A. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.

    2018-04-01

    The cerebral cortex plays a key role in complex cortical functions. It can be divided into areas according to their function (motor, sensory and association areas). In this paper, the cerebral cortex is described as a network of networks (cortex network), we consider that each cortical area is composed of a network with small-world property (cortical network). The neurons are assumed to have bursting properties with the dynamics described by the Rulkov model. We study the phase synchronization of the cortex network and the cortical networks. In our simulations, we verify that synchronization in cortex network is not homogeneous. Besides, we focus on the suppression of neural phase synchronization. Synchronization can be related to undesired and pathological abnormal rhythms in the brain. For this reason, we consider the delayed feedback control to suppress the synchronization. We show that delayed feedback control is efficient to suppress synchronous behavior in our network model when an appropriate signal intensity and time delay are defined.

  12. Sleep Deprivation Makes the Young Brain Resemble the Elderly Brain: A Large-Scale Brain Networks Study.

    Science.gov (United States)

    Zhou, Xinqi; Wu, Taoyu; Yu, Jing; Lei, Xu

    2017-02-01

    Decreased cognition performance and impaired brain function are similar results of sleep deprivation (SD) and aging, according to mounted supporting evidence. Some investigators even proposed SD as a model of aging. However, few direct comparisons were ever explored between the effects of SD and aging by network module analysis with the resting-state functional magnetic resonance imaging. In this study, both within-module and between-module (BT) connectivities were calculated in the whole brain to describe a complete picture of brain networks' functional connectivity among three groups (young normal sleep, young SD, and old group). The results showed that the BT connectivities in subcortical and cerebellar networks were significantly declined in both the young SD group and old group. There were six other networks, that is, ventral attention, dorsal attention, default mode, auditory, cingulo-opercular, and memory retrieval networks, significantly influenced by aging. Therefore, we speculated that the effects of SD on the young group can be regarded as a simplified model of aging. Moreover, this provided a possible explanation, that is, the old were more tolerable for SD than the young. However, SD may not be a considerable model for aging when discussing the brain regions related to those SD-uninfluenced networks.

  13. Predictors of longitudinal outcome and recovery of pragmatic language and its relation to externalizing behaviour after pediatric traumatic brain injury.

    Science.gov (United States)

    Ryan, Nicholas P; Catroppa, Cathy; Beare, Richard; Coleman, Lee; Ditchfield, Michael; Crossley, Louise; Beauchamp, Miriam H; Anderson, Vicki A

    2015-03-01

    The purpose of the present investigation was to evaluate the contribution of age-at-insult and brain pathology on longitudinal outcome and recovery of pragmatic language in a sample of children and adolescents with traumatic brain injury (TBI). Children and adolescents with mild to severe TBI (n=112) were categorized according to timing of brain insult: (i) Middle Childhood (5-9 years; n=41); (ii) Late Childhood (10-11 years; n=39); and (iii) Adolescence (12-15 years; n=32) and group-matched for age, gender and socio-economic status (SES) to a typically developing (TD) control group (n=43). Participants underwent magnetic resonance imaging (MRI) including a susceptibility weighted imaging (SWI) sequence 2-8 weeks after injury and were assessed on measures of pragmatic language and behavioural functioning at 6- and 24-months after injury. Children and adolescents with TBI of all severity levels demonstrated impairments in these domains at 6-months injury before returning to age-expected levels at 2-years post-TBI. However, while adolescent TBI was associated with post-acute disruption to skills that preceded recovery to age-expected levels by 2-years post injury, the middle childhood TBI group demonstrated impairments at 6-months post-injury that were maintained at 2-year follow up. Reduced pragmatic communication was associated with frontal, temporal and corpus callosum lesions, as well as more frequent externalizing behaviour at 24-months post injury. Findings show that persisting pragmatic language impairment after pediatric TBI is related to younger age at brain insult, as well as microhemorrhagic pathology in brain regions that contribute to the anatomically distributed social brain network. Relationships between reduced pragmatic communication and more frequent externalizing behavior underscore the need for context-sensitive rehabilitation programs that aim to increase interpersonal effectiveness and reduce risk for maladaptive behavior trajectories into the

  14. Plasticity in the developing brain: intellectual, language and academic functions in children with ischaemic perinatal stroke

    OpenAIRE

    Ballantyne, Angela O.; Spilkin, Amy M.; Hesselink, John; Trauner, Doris A.

    2008-01-01

    The developing brain has the capacity for a great deal of plasticity. A number of investigators have demonstrated that intellectual and language skills may be in the normal range in children following unilateral perinatal stroke. Questions have been raised, however, about whether these skills can be maintained at the same level as the brain matures. This study aimed to examine the stability of intellectual, academic and language functioning during development in children with perinatal stroke...

  15. Supervised dictionary learning for inferring concurrent brain networks.

    Science.gov (United States)

    Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming

    2015-10-01

    Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.

  16. Frequency-specific network topologies in the resting human brain

    Directory of Open Access Journals (Sweden)

    Shuntaro eSasai

    2014-12-01

    Full Text Available A community is a set of nodes with dense inter-connections, while there are sparse connections between different communities. A hub is a highly connected node with high centrality. It has been shown that both communities and hubs exist simultaneously in the brain’s functional connectivity network, as estimated by correlations among low-frequency spontaneous fluctuations in functional magnetic resonance imaging (fMRI signal changes (0.01–0.10 Hz. This indicates that the brain has a spatial organization that promotes both segregation and integration of information. Here, we demonstrate that frequency-specific network topologies that characterize segregation and integration also exist within this frequency range. In investigating the coherence spectrum among 87 brain regions, we found that two frequency bands, 0.01–0.03 Hz (very low frequency [VLF] band and 0.07–0.09 Hz (low frequency [LF] band, mainly contributed to functional connectivity. Comparing graph theoretical indices for the VLF and LF bands revealed that the network in the former had a higher capacity for information segregation between identified communities than the latter. Hubs in the VLF band were mainly located within the anterior cingulate cortices, whereas those in the LF band were located in the posterior cingulate cortices and thalamus. Thus, depending on the timescale of brain activity, at least two distinct network topologies contributed to information segregation and integration. This suggests that the brain intrinsically has timescale-dependent functional organizations.

  17. Patterns recognition of electric brain activity using artificial neural networks

    Science.gov (United States)

    Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

    2017-04-01

    An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

  18. 5-HTTLPR differentially predicts brain network responses to emotional faces

    DEFF Research Database (Denmark)

    Fisher, Patrick M; Grady, Cheryl L; Madsen, Martin K

    2015-01-01

    The effects of the 5-HTTLPR polymorphism on neural responses to emotionally salient faces have been studied extensively, focusing on amygdala reactivity and amygdala-prefrontal interactions. Despite compelling evidence that emotional face paradigms engage a distributed network of brain regions...... to fearful faces was significantly greater in S' carriers compared to LA LA individuals. These findings provide novel evidence for emotion-specific 5-HTTLPR effects on the response of a distributed set of brain regions including areas responsive to emotionally salient stimuli and critical components...... involved in emotion, cognitive and visual processing, less is known about 5-HTTLPR effects on broader network responses. To address this, we evaluated 5-HTTLPR differences in the whole-brain response to an emotional faces paradigm including neutral, angry and fearful faces using functional magnetic...

  19. Evidence of a Christmas spirit network in the brain

    DEFF Research Database (Denmark)

    Hougaard, Anders; Lindberg, Ulrich; Arngrim, Nanna

    2015-01-01

    OBJECTIVE: To detect and localise the Christmas spirit in the human brain. DESIGN: Single blinded, cross cultural group study with functional magnetic resonance imaging (fMRI). SETTING: Functional imaging unit and department of clinical physiology, nuclear medicine and PET in Denmark. PARTICIPANTS...... theme. METHODS: Functional brain scans optimised for detection of the blood oxygen level dependent (BOLD) response were performed while participants viewed a series of images with Christmas themes interleaved with neutral images having similar characteristics but containing nothing that symbolises...... spirit network" in the human brain comprising several cortical areas. This network had a significantly higher activation in a people who celebrate Christmas with positive associations as opposed to a people who have no Christmas traditions and neutral associations. Further research is necessary...

  20. Brain dynamics in the comprehension of action-related language. A time-frequency analysis of mu rhythms.

    Science.gov (United States)

    Moreno, Iván; de Vega, Manuel; León, Inmaculada; Bastiaansen, Marcel; Glen Lewis, Ashley; Magyari, Lilla

    2015-04-01

    EEG mu rhythms (8-13 Hz) recorded at fronto-central electrodes are generally considered as markers of motor cortical activity in humans, because they are modulated when participants perform an action, when they observe another's action or even when they imagine performing an action. In this study, we analyzed the time-frequency (TF) modulation of mu rhythms while participants read action language ("You will cut the strawberry cake"), abstract language ("You will doubt the patient's argument"), and perceptive language ("You will notice the bright day"). The results indicated that mu suppression at fronto-central sites is associated with action language rather than with abstract or perceptive language. Also, the largest difference between conditions occurred quite late in the sentence, while reading the first noun, (contrast Action vs. Abstract), or the second noun following the action verb (contrast Action vs. Perceptive). This suggests that motor activation is associated with the integration of words across the sentence beyond the lexical processing of the action verb. Source reconstruction localized mu suppression associated with action sentences in premotor cortex (BA 6). The present study suggests (1) that the understanding of action language activates motor networks in the human brain, and (2) that this activation occurs online based on semantic integration across multiple words in the sentence. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Speaking in Multiple Languages: Neural Correlates of Language Proficiency in Multilingual Word Production

    Science.gov (United States)

    Videsott, Gerda; Herrnberger, Barbel; Hoenig, Klaus; Schilly, Edgar; Grothe, Jo; Wiater, Werner; Spitzer, Manfred; Kiefer, Markus

    2010-01-01

    The human brain has the fascinating ability to represent and to process several languages. Although the first and further languages activate partially different brain networks, the linguistic factors underlying these differences in language processing have to be further specified. We investigated the neural correlates of language proficiency in a…

  2. Sex differences in normal age trajectories of functional brain networks.

    Science.gov (United States)

    Scheinost, Dustin; Finn, Emily S; Tokoglu, Fuyuze; Shen, Xilin; Papademetris, Xenophon; Hampson, Michelle; Constable, R Todd

    2015-04-01

    Resting-state functional magnetic resonance image (rs-fMRI) is increasingly used to study functional brain networks. Nevertheless, variability in these networks due to factors such as sex and aging is not fully understood. This study explored sex differences in normal age trajectories of resting-state networks (RSNs) using a novel voxel-wise measure of functional connectivity, the intrinsic connectivity distribution (ICD). Males and females showed differential patterns of changing connectivity in large-scale RSNs during normal aging from early adulthood to late middle-age. In some networks, such as the default-mode network, males and females both showed decreases in connectivity with age, albeit at different rates. In other networks, such as the fronto-parietal network, males and females showed divergent connectivity trajectories with age. Main effects of sex and age were found in many of the same regions showing sex-related differences in aging. Finally, these sex differences in aging trajectories were robust to choice of preprocessing strategy, such as global signal regression. Our findings resolve some discrepancies in the literature, especially with respect to the trajectory of connectivity in the default mode, which can be explained by our observed interactions between sex and aging. Overall, results indicate that RSNs show different aging trajectories for males and females. Characterizing effects of sex and age on RSNs are critical first steps in understanding the functional organization of the human brain. © 2014 Wiley Periodicals, Inc.

  3. Flow distributions and spatial correlations in human brain capillary networks

    Science.gov (United States)

    Lorthois, Sylvie; Peyrounette, Myriam; Larue, Anne; Le Borgne, Tanguy

    2015-11-01

    The vascular system of the human brain cortex is composed of a space filling mesh-like capillary network connected upstream and downstream to branched quasi-fractal arterioles and venules. The distribution of blood flow rates in these networks may affect the efficiency of oxygen transfer processes. Here, we investigate the distribution and correlation properties of blood flow velocities from numerical simulations in large 3D human intra-cortical vascular network (10000 segments) obtained from an anatomical database. In each segment, flow is solved from a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation to deduce blood pressure, blood flow and red blood cell volume fraction distributions throughout the network. The network structural complexity is found to impart broad and spatially correlated Lagrangian velocity distributions, leading to power law transit time distributions. The origins of this behavior (existence of velocity correlations in capillary networks, influence of the coupling with the feeding arterioles and draining veins, topological disorder, complex blood rheology) are studied by comparison with results obtained in various model capillary networks of controlled disorder. ERC BrainMicroFlow GA615102, ERC ReactiveFronts GA648377.

  4. Cortical network architecture for context processing in primate brain.

    Science.gov (United States)

    Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka

    2015-09-29

    Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition.

  5. Structural brain network: What is the effect of LiFE optimization of whole brain tractography?

    Directory of Open Access Journals (Sweden)

    Shouliang eQi

    2016-02-01

    Full Text Available Structural brain networks constructed based on diffusion-weighted MRI (dMRI have provided a systems perspective to explore the organization of the human brain. Some redundant and nonexistent fibers, however, are inevitably generated in whole brain tractography. We propose to add one critical step while constructing the networks to remove these fibers using the linear fascicle evaluation (LiFE method, and study the differences between the networks with and without LiFE optimization. For a cohort of 9 healthy adults and for 9 out of the 35 subjects from Human Connectome Project, the T1-weighted images and dMRI data are analyzed. Each brain is parcellated into 90 regions-of-interest, whilst a probabilistic tractography algorithm is applied to generate the original connectome. The elimination of redundant and nonexistent fibers from the original connectome by LiFE creates the optimized connectome, and the random selection of the same number of fibers as the optimized connectome creates the non-optimized connectome. The combination of parcellations and these connectomes leads to the optimized and non-optimized networks, respectively. The optimized networks are constructed with six weighting schemes, and the correlations of different weighting methods are analyzed. The fiber length distributions of the non-optimized and optimized connectomes are compared. The optimized and non-optimized networks are compared with regard to edges, nodes and networks, within a sparsity range of 0.75-0.95. It has been found that relatively more short fibers exist in the optimized connectome. About 24.0% edges of the optimized network are significantly different from those in the non-optimized network at a sparsity of 0.75. About 13.2% of edges are classified as false positives or the possible missing edges. The strength and betweenness centrality of some nodes are significantly different for the non-optimized and optimized networks, but not the node efficiency. The

  6. Mnemonic Training Reshapes Brain Networks to Support Superior Memory.

    Science.gov (United States)

    Dresler, Martin; Shirer, William R; Konrad, Boris N; Müller, Nils C J; Wagner, Isabella C; Fernández, Guillén; Czisch, Michael; Greicius, Michael D

    2017-03-08

    Memory skills strongly differ across the general population; however, little is known about the brain characteristics supporting superior memory performance. Here we assess functional brain network organization of 23 of the world's most successful memory athletes and matched controls with fMRI during both task-free resting state baseline and active memory encoding. We demonstrate that, in a group of naive controls, functional connectivity changes induced by 6 weeks of mnemonic training were correlated with the network organization that distinguishes athletes from controls. During rest, this effect was mainly driven by connections between rather than within the visual, medial temporal lobe and default mode networks, whereas during task it was driven by connectivity within these networks. Similarity with memory athlete connectivity patterns predicted memory improvements up to 4 months after training. In conclusion, mnemonic training drives distributed rather than regional changes, reorganizing the brain's functional network organization to enable superior memory performance. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Pro-cognitive drug effects modulate functional brain network organization

    Directory of Open Access Journals (Sweden)

    Carsten eGiessing

    2012-08-01

    Full Text Available Previous studies document that cholinergic and noradrenergic drugs improve attention, memory and cognitive control in healthy subjects and patients with neuropsychiatric disorders. In humans neural mechanisms of cholinergic and noradrenergic modulation have mainly been analyzed by investigating drug-induced changes of task-related neural activity measured with fMRI. Endogenous neural activity has often been neglected. Further, although drugs affect the coupling between neurons, only a few human studies have explicitly addressed how drugs modulate the functional connectome, i.e. the functional neural interactions within the brain. These studies have mainly focused on synchronization or correlation of brain activations. Recently, there are some drug studies using graph theory and other new mathematical approaches to model the brain as a complex network of interconnected processing nodes. Using such measures it is possible to detect not only focal, but also subtle, widely distributed drug effects on functional network topology. Most important, graph theoretical measures also quantify whether drug-induced changes in topology or network organization facilitate or hinder information processing. Several studies could show that functional brain integration is highly correlated with behavioral performance suggesting that cholinergic and noradrenergic drugs which improve measures of cognitive performance should increase functional network integration. The purpose of this paper is to show that graph theory provides a mathematical tool to develop theory-driven biomarkers of pro-cognitive drug effects, and also to discuss how these approaches can contribute to the understanding of the role of cholinergic and noradrenergic modulation in the human brain. Finally we discuss the global workspace theory as a theoretical framework of pro-cognitive drug effects and argue that pro-cognitive effects of cholinergic and noradrenergic drugs might be related to higher

  8. Pro-cognitive drug effects modulate functional brain network organization

    Science.gov (United States)

    Giessing, Carsten; Thiel, Christiane M.

    2012-01-01

    Previous studies document that cholinergic and noradrenergic drugs improve attention, memory and cognitive control in healthy subjects and patients with neuropsychiatric disorders. In humans neural mechanisms of cholinergic and noradrenergic modulation have mainly been analyzed by investigating drug-induced changes of task-related neural activity measured with functional magnetic resonance imaging (fMRI). Endogenous neural activity has often been neglected. Further, although drugs affect the coupling between neurons, only a few human studies have explicitly addressed how drugs modulate the functional connectome, i.e., the functional neural interactions within the brain. These studies have mainly focused on synchronization or correlation of brain activations. Recently, there are some drug studies using graph theory and other new mathematical approaches to model the brain as a complex network of interconnected processing nodes. Using such measures it is possible to detect not only focal, but also subtle, widely distributed drug effects on functional network topology. Most important, graph theoretical measures also quantify whether drug-induced changes in topology or network organization facilitate or hinder information processing. Several studies could show that functional brain integration is highly correlated with behavioral performance suggesting that cholinergic and noradrenergic drugs which improve measures of cognitive performance should increase functional network integration. The purpose of this paper is to show that graph theory provides a mathematical tool to develop theory-driven biomarkers of pro-cognitive drug effects, and also to discuss how these approaches can contribute to the understanding of the role of cholinergic and noradrenergic modulation in the human brain. Finally we discuss the “global workspace” theory as a theoretical framework of pro-cognitive drug effects and argue that pro-cognitive effects of cholinergic and noradrenergic drugs

  9. Structural network analysis of brain development in young preterm neonates.

    Science.gov (United States)

    Brown, Colin J; Miller, Steven P; Booth, Brian G; Andrews, Shawn; Chau, Vann; Poskitt, Kenneth J; Hamarneh, Ghassan

    2014-11-01

    Preterm infants develop differently than those born at term and are at higher risk of brain pathology. Thus, an understanding of their development is of particular importance. Diffusion tensor imaging (DTI) of preterm infants offers a window into brain development at a very early age, an age at which that development is not yet fully understood. Recent works have used DTI to analyze structural connectome of the brain scans using network analysis. These studies have shown that, even from infancy, the brain exhibits small-world properties. Here we examine a cohort of 47 normal preterm neonates (i.e., without brain injury and with normal neurodevelopment at 18 months of age) scanned between 27 and 45 weeks post-menstrual age to further the understanding of how the structural connectome develops. We use full-brain tractography to find white matter tracts between the 90 cortical and sub-cortical regions defined in the University of North Carolina Chapel Hill neonatal atlas. We then analyze the resulting connectomes and explore the differences between weighting edges by tract count versus fractional anisotropy. We observe that the brain networks in preterm infants, much like infants born at term, show high efficiency and clustering measures across a range of network scales. Further, the development of many individual region-pair connections, particularly in the frontal and occipital lobes, is significantly correlated with age. Finally, we observe that the preterm infant connectome remains highly efficient yet becomes more clustered across this age range, leading to a significant increase in its small-world structure. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. Neurolinguistic Annotated Bibliography (Brain Research and Language Function) with Implications for Education.

    Science.gov (United States)

    Davis, Wesley K.

    This bibliography presents annotations of 91 journal articles, books, chapters in books, and conference papers dating from 1967 to 1984 concerning neurolinguistics, language processing, and educational implications of brain research. The annotated bibliography includes eight items on neuroanatomy and language function; 20 items on neurolinguistics…

  11. Co-Localisation of Abnormal Brain Structure and Function in Specific Language Impairment

    Science.gov (United States)

    Badcock, Nicholas A.; Bishop, Dorothy V. M.; Hardiman, Mervyn J.; Barry, Johanna G.; Watkins, Kate E.

    2012-01-01

    We assessed the relationship between brain structure and function in 10 individuals with specific language impairment (SLI), compared to six unaffected siblings, and 16 unrelated control participants with typical language. Voxel-based morphometry indicated that grey matter in the SLI group, relative to controls, was increased in the left inferior…

  12. Meeting the memory challenges of brain-scale network simulation

    Directory of Open Access Journals (Sweden)

    Susanne eKunkel

    2012-01-01

    Full Text Available The development of high-performance simulation software is crucial for studying the brain connectome. Using connectome data to generate neurocomputational models requires software capable of coping with models on a variety of scales: from the microscale, investigating plasticity and dynamics of circuits in local networks, to the macroscale, investigating the interactions between distinct brain regions. Prior to any serious dynamical investigation, the first task of network simulations is to check the consistency of data integrated in the connectome and constrain ranges for yet unknown parameters. Thanks to distributed computing techniques, it is possible today to routinely simulate local cortical networks of around 10^5 neurons with up to 10^9 synapses on clusters and multi-processor shared-memory machines. However, brain-scale networks are one or two orders of magnitude larger than such local networks, in terms of numbers of neurons and synapses as well as in terms of computational load. Such networks have been studied in individual studies, but the underlying simulation technologies have neither been described in sufficient detail to be reproducible nor made publicly available. Here, we discover that as the network model sizes approach the regime of meso- and macroscale simulations, memory consumption on individual compute nodes becomes a critical bottleneck. This is especially relevant on modern supercomputers such as the Bluegene/P architecture where the available working memory per CPU core is rather limited. We develop a simple linear model to analyze the memory consumption of the constituent components of a neuronal simulator as a function of network size and the number of cores used. This approach has multiple benefits. The model enables identification of key contributing components to memory saturation and prediction of the effects of potential improvements to code before any implementation takes place.

  13. Lectures in Supercomputational Neurosciences Dynamics in Complex Brain Networks

    CERN Document Server

    Graben, Peter beim; Thiel, Marco; Kurths, Jürgen

    2008-01-01

    Computational Neuroscience is a burgeoning field of research where only the combined effort of neuroscientists, biologists, psychologists, physicists, mathematicians, computer scientists, engineers and other specialists, e.g. from linguistics and medicine, seem to be able to expand the limits of our knowledge. The present volume is an introduction, largely from the physicists' perspective, to the subject matter with in-depth contributions by system neuroscientists. A conceptual model for complex networks of neurons is introduced that incorporates many important features of the real brain, such as various types of neurons, various brain areas, inhibitory and excitatory coupling and the plasticity of the network. The computational implementation on supercomputers, which is introduced and discussed in detail in this book, will enable the readers to modify and adapt the algortihm for their own research. Worked-out examples of applications are presented for networks of Morris-Lecar neurons to model the cortical co...

  14. Mapping Language Function in the Brain: A Review of the Recent Literature.

    Science.gov (United States)

    Crafton, Robert E.; Kido, Elissa

    2000-01-01

    Considers the potential importance of brain study for composition instruction, briefly describes functional imaging techniques, and reviews the findings of recent brain-mapping studies investigating the neurocognitive systems involved in language function. Presents a review of the recent literature and considers the possible implications of this…

  15. Shadows of Music-Language Interaction on Low Frequency Brain Oscillatory Patterns

    Science.gov (United States)

    Carrus, Elisa; Koelsch, Stefan; Bhattacharya, Joydeep

    2011-01-01

    Electrophysiological studies investigating similarities between music and language perception have relied exclusively on the signal averaging technique, which does not adequately represent oscillatory aspects of electrical brain activity that are relevant for higher cognition. The current study investigated the patterns of brain oscillations…

  16. Statistical physics, neural networks, brain studies

    International Nuclear Information System (INIS)

    Toulouse, G.

    1999-01-01

    An overview of some aspects of a vast domain, located at the crossroads of physics, biology and computer science is presented: (1) During the last fifteen years, physicists advancing along various pathways have come into contact with biology (computational neurosciences) and engineering (formal neural nets). (2) This move may actually be viewed as one component in a larger picture. A prominent trend of recent years, observable over many countries, has been the establishment of interdisciplinary centers devoted to the study of: cognitive sciences; natural and artificial intelligence; brain, mind and behaviour; perception and action; learning and memory; robotics; man-machine communication, etc. What are the promising lines of development? What opportunities for physicists? An attempt will be made to address such questions and related issues

  17. Clinical standardized fMRI reveals altered language lateralization in patients with brain tumor.

    Science.gov (United States)

    Partovi, S; Jacobi, B; Rapps, N; Zipp, L; Karimi, S; Rengier, F; Lyo, J K; Stippich, C

    2012-12-01

    Brain tumors affecting language-relevant areas may influence language lateralization. The purpose of this study was to systematically investigate language lateralization in brain tumor patients using clinical language fMRI, comparing the results with a group of healthy volunteers. Fifty-seven strictly right-handed patients with left-hemispheric-space intracranial masses (mainly neoplastic) affecting either the Broca area (n = 19) or Wernicke area (n = 38) were prospectively enrolled in this study. Fourteen healthy volunteers served as a control group. Standardized clinical language fMRI, using visually triggered sentence- and word-generation paradigms, was performed on a 1.5T MR scanner. Semiautomated analyses of all functional data were conducted on an individual basis using BrainVoyager. A regional lateralization index was calculated for Broca and Wernicke areas separately versus their corresponding right-hemisphere homologs. In masses affecting the Broca area, a significant decrease in the lateralization index was found when performing word generation (P = .0017), whereas when applying sentence generation, the decrease did not reach statistical significance (P = .851). Masses affecting the Wernicke area induced a significant decrease of the lateralization index when performing sentence generation (P = .0007), whereas when applying word generation, the decrease was not statistically significant (P = .310). Clinical language fMRI was feasible for patients with brain tumors and provided relevant presurgical information by localizing essential language areas and determining language dominance. A significant effect of the brain masses on language lateralization was observed, with a shift toward the contralesional, nondominant hemisphere. This may reflect compensatory mechanisms of the brain to maintain communicative abilities.

  18. Lexical issues of UNL universal networking language 2012 panel

    CERN Document Server

    Martins, Ronaldo

    2013-01-01

    This book inaugurates a series of discussions on what is permanent in the original thinking of the UNL - Universal Networking Language - and the changes that have been introduced during its development. The purpose of the book is to highlight the UNL's fundamental principles that remain as integral as they were when they were first formulated several years ago, while showing how their materialization has evolved over time, following the advances in Linguistics, Knowledge Engineering and Information Sciences. The fundamental and unchanged principles of the UNL are: the idea of an artificial lan

  19. Reprint of "Does Functional Neuroimaging Solve the Questions of Neurolinguistics?" [Brain and Language 98 (2006) 276-290

    Science.gov (United States)

    Van Lancker Sidtis, Diana

    2007-01-01

    Neurolinguistic research has been engaged in evaluating models of language using measures from brain structure and function, and/or in investigating brain structure and function with respect to language representation using proposed models of language. While the aphasiological strategy, which classifies aphasias based on performance modality and a…

  20. Default Mode Network, Motor Network, Dorsal and Ventral Basal Ganglia Networks in the Rat Brain: Comparison to Human Networks Using Resting State-fMRI

    Science.gov (United States)

    Sierakowiak, Adam; Monnot, Cyril; Aski, Sahar Nikkhou; Uppman, Martin; Li, Tie-Qiang; Damberg, Peter; Brené, Stefan

    2015-01-01

    Rodent models are developed to enhance understanding of the underlying biology of different brain disorders. However, before interpreting findings from animal models in a translational aspect to understand human disease, a fundamental step is to first have knowledge of similarities and differences of the biological systems studied. In this study, we analyzed and verified four known networks termed: default mode network, motor network, dorsal basal ganglia network, and ventral basal ganglia network using resting state functional MRI (rsfMRI) in humans and rats. Our work supports the notion that humans and rats have common robust resting state brain networks and that rsfMRI can be used as a translational tool when validating animal models of brain disorders. In the future, rsfMRI may be used, in addition to short-term interventions, to characterize longitudinal effects on functional brain networks after long-term intervention in humans and rats. PMID:25789862

  1. Association between functional connectivity hubs and brain networks.

    Science.gov (United States)

    Tomasi, Dardo; Volkow, Nora D

    2011-09-01

    Functional networks are usually accessed with "resting-state" functional magnetic resonance imaging using preselected "seeds" regions. Frequently, however, the selection of the seed locations is arbitrary. Recently, we proposed local functional connectivity density mapping (FCDM), an ultrafast data-driven to locate highly connected brain regions (functional hubs). Here, we used the functional hubs obtained from local FCDM to determine the functional networks of the resting state in 979 healthy subjects without a priori hypotheses on seed locations. In addition, we computed the global functional connectivity hubs. Seven networks covering 80% of the gray matter volume were identified. Four major cortical hubs (ventral precuneus/posterior cingulate, inferior parietal cortex, cuneus, and postcentral gyrus) were linked to 4 cortical networks (default mode, dorsal attention, visual, and somatosensory). Three subcortical networks were associated to the major subcortical hubs (cerebellum, thalamus, and amygdala). The networks differed in their resting activity and topology. The higher coupling and overlap of subcortical networks was associated to higher contribution of short-range functional connectivity in thalamus and cerebellum. Whereas cortical local FCD hubs were also hubs of long-range connectivity, which corroborates the key role of cortical hubs in network architecture, subcortical hubs had minimal long-range connectivity. The significant variability among functional networks may underlie their sensitivity/resilience to neuropathology.

  2. Cross-linguistic influence of first language writing systems on brain responses to second language word reading in late bilinguals.

    Science.gov (United States)

    Yokoyama, Satoru; Kim, Jungho; Uchida, Shinya; Miyamoto, Tadao; Yoshimoto, Kei; Kawashima, Ryuta

    2013-09-01

    Introduction How human brains acquire second languages (L2) is one of the fundamental questions in neuroscience and language science. However, it is unclear whether the first language (L1) has a cross-linguistic influence on the processing of L2. Methods Here, we used functional magnetic resonance imaging to compare brain activities during L2 word reading tasks of phonographic Japanese Kana between two groups of learners of the Japanese language as their L2 and who had different orthographic backgrounds of their L1. For Chinese learners, a L1 of the Chinese language (Hanji) and a L2 of the Japanese Kana differed orthographically, whereas for Korean learners, a L1 of Korean Hangul and a L2 of Japanese Kana were similar. Results Our analysis revealed that, although proficiency and the age of acquisition did not differ between the two groups, Chinese learners showed greater activation of the left middle frontal gyrus than Korean learners during L2 word reading. Conclusion Our results provide evidence that strongly supported the hypothesis that cross-linguistic variations in orthography between L1 and L2 induce differential brain activation during L2 word reading, which has been proposed previously.

  3. Mapping human brain networks with cortico-cortical evoked potentials

    Science.gov (United States)

    Keller, Corey J.; Honey, Christopher J.; Mégevand, Pierre; Entz, Laszlo; Ulbert, Istvan; Mehta, Ashesh D.

    2014-01-01

    The cerebral cortex forms a sheet of neurons organized into a network of interconnected modules that is highly expanded in humans and presumably enables our most refined sensory and cognitive abilities. The links of this network form a fundamental aspect of its organization, and a great deal of research is focusing on understanding how information flows within and between different regions. However, an often-overlooked element of this connectivity regards a causal, hierarchical structure of regions, whereby certain nodes of the cortical network may exert greater influence over the others. While this is difficult to ascertain non-invasively, patients undergoing invasive electrode monitoring for epilepsy provide a unique window into this aspect of cortical organization. In this review, we highlight the potential for cortico-cortical evoked potential (CCEP) mapping to directly measure neuronal propagation across large-scale brain networks with spatio-temporal resolution that is superior to traditional neuroimaging methods. We first introduce effective connectivity and discuss the mechanisms underlying CCEP generation. Next, we highlight how CCEP mapping has begun to provide insight into the neural basis of non-invasive imaging signals. Finally, we present a novel approach to perturbing and measuring brain network function during cognitive processing. The direct measurement of CCEPs in response to electrical stimulation represents a potentially powerful clinical and basic science tool for probing the large-scale networks of the human cerebral cortex. PMID:25180306

  4. A Programming Language Approach to Safety in Home Networks

    DEFF Research Database (Denmark)

    Mortensen, Kjeld Høyer; Schougaard, Kari Rye; Schultz, Ulrik Pagh

    Home networks and the interconnection of home appliances is a classical theme in pervasive computing research. Security is usually addressed through the use of encryption and authentication, but there is a lack of awareness of safety: reventing the computerized house from harming the inhabitants......, even in a worst-case scenario where an unauthorized user gains remote control of the facilities. We address this safety issue at the programming language level by restricting the operations that can be performed on devices according to the physical location of the user initiating the request......-based restrictions on operations. This model has been implemented in a middleware for home AV devices written in Java, using infrared communication and a FireWire network to implement location awareness....

  5. A Programming Language Approach to Safety in Home Networks

    DEFF Research Database (Denmark)

    Mortensen, Kjeld Høyer; Schougaard, Kari Sofie Fogh; Schultz, Ulrik Pagh

    2003-01-01

    Home networks and the interconnection of home appliances is a classical theme in pervasive computing research. Security is usually addressed through the use of encryption and authentication, but there is a lack of awareness of safety: preventing the computerized house from harming the inhabitants......, even in a worst-case scenario where an unauthorized user gains remote control of the facilities. We address this safety issue at the programming language level by restricting the operations that can be performed on devices according to the physical location of the user initiating the request......-based restrictions on operations. This model has been implemented in a middleware for home AV devices written in Java, using infrared communication and a FireWire network to implement location awareness....

  6. Loss of brain graph network efficiency in alcohol dependence.

    Science.gov (United States)

    Sjoerds, Zsuzsika; Stufflebeam, Steven M; Veltman, Dick J; Van den Brink, Wim; Penninx, Brenda W J H; Douw, Linda

    2017-03-01

    Alcohol dependence (AD) is characterized by corticostriatal impairments in individual brain areas such as the striatum. As yet however, complex brain network topology in AD and its association with disease progression are unknown. We applied graph theory to resting-state functional magnetic resonance imaging (RS-fMRI) to examine weighted global efficiency and local (clustering coefficient, degree and eigenvector centrality) network topology and the functional role of the striatum in 24 AD patients compared with 20 matched healthy controls (HCs), and their association with dependence characteristics. Graph analyses were performed based on Pearson's correlations between RS-fMRI time series, while correcting for age, gender and head motion. We found no significant group differences between AD patients and HCs in network topology. Notably, within the patient group, but not in HCs, the whole-brain network showed reduced average cluster coefficient with more severe alcohol use, whereas longer AD duration within the patient group was associated with a global decrease in efficiency, degree and clustering coefficient. Additionally, within four a-priori chosen bilateral striatal nodes, alcohol use severity was associated with lower clustering coefficient in the left caudate. Longer AD duration was associated with reduced clustering coefficient in caudate and putamen, and reduced degree in bilateral caudate, but with increased eigenvector centrality in left posterior putamen. Especially changes in global network topology and clustering coefficient in anterior striatum remained strikingly robust after exploratory variations in network weight. Our results show adverse effects of AD on overall network integration and possibly on striatal efficiency, putatively contributing to the increasing behavioral impairments seen in chronically addicted patients. © 2015 Society for the Study of Addiction.

  7. Age of language acquisition and cortical language organization in multilingual patients undergoing awake brain mapping.

    Science.gov (United States)

    Fernández-Coello, Alejandro; Havas, Viktória; Juncadella, Montserrat; Sierpowska, Joanna; Rodríguez-Fornells, Antoni; Gabarrós, Andreu

    2017-06-01

    OBJECTIVE Most knowledge regarding the anatomical organization of multilingualism is based on aphasiology and functional imaging studies. However, the results have still to be validated by the gold standard approach, namely electrical stimulation mapping (ESM) during awake neurosurgical procedures. In this ESM study the authors describe language representation in a highly specific group of 13 multilingual individuals, focusing on how age of acquisition may influence the cortical organization of language. METHODS Thirteen patients who had a high degree of proficiency in multiple languages and were harboring lesions within the dominant, left hemisphere underwent ESM while being operated on under awake conditions. Demographic and language data were recorded in relation to age of language acquisition (for native languages and early- and late-acquired languages), neuropsychological pre- and postoperative language testing, the number and location of language sites, and overlapping distribution in terms of language acquisition time. Lesion growth patterns and histopathological characteristics, location, and size were also recorded. The distribution of language sites was analyzed with respect to age of acquisition and overlap. RESULTS The functional language-related sites were distributed in the frontal (55%), temporal (29%), and parietal lobes (16%). The total number of native language sites was 47. Early-acquired languages (including native languages) were represented in 97 sites (55 overlapped) and late-acquired languages in 70 sites (45 overlapped). The overlapping distribution was 20% for early-early, 71% for early-late, and 9% for late-late. The average lesion size (maximum diameter) was 3.3 cm. There were 5 fast-growing and 7 slow-growing lesions. CONCLUSIONS Cortical language distribution in multilingual patients is not homogeneous, and it is influenced by age of acquisition. Early-acquired languages have a greater cortical representation than languages acquired

  8. Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks.

    Science.gov (United States)

    Vértes, Petra E; Alexander-Bloch, Aaron; Bullmore, Edward T

    2014-10-05

    Rich clubs arise when nodes that are 'rich' in connections also form an elite, densely connected 'club'. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be driven by an economic trade-off between connection costs and a second, competing topological term. Secondly we show, using simulated neural networks, that Hebbian learning rules also drive the emergence of rich clubs at the microscopic level, and that the prominence of these features increases with learning time. These results suggest that Hebbian learning may provide a neuronal mechanism for the selection of complex features such as rich clubs. The neural networks that we investigate are explicitly Hebbian, and we argue that the topological term in our model of large-scale brain connectivity may represent an analogous connection rule. This putative link between learning and rich clubs is also consistent with predictions that integrative aspects of brain network organization are especially important for adaptive behaviour. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  9. Multilayer modeling and analysis of human brain networks.

    Science.gov (United States)

    De Domenico, Manlio

    2017-05-01

    Understanding how the human brain is structured, and how its architecture is related to function, is of paramount importance for a variety of applications, including but not limited to new ways to prevent, deal with, and cure brain diseases, such as Alzheimer's or Parkinson's, and psychiatric disorders, such as schizophrenia. The recent advances in structural and functional neuroimaging, together with the increasing attitude toward interdisciplinary approaches involving computer science, mathematics, and physics, are fostering interesting results from computational neuroscience that are quite often based on the analysis of complex network representation of the human brain. In recent years, this representation experienced a theoretical and computational revolution that is breaching neuroscience, allowing us to cope with the increasing complexity of the human brain across multiple scales and in multiple dimensions and to model structural and functional connectivity from new perspectives, often combined with each other. In this work, we will review the main achievements obtained from interdisciplinary research based on magnetic resonance imaging and establish de facto, the birth of multilayer network analysis and modeling of the human brain. © The Author 2017. Published by Oxford University Press.

  10. Abnormal Brain Network Organization in Body Dysmorphic Disorder

    Science.gov (United States)

    Arienzo, Donatello; Leow, Alex; Brown, Jesse A; Zhan, Liang; GadElkarim, Johnson; Hovav, Sarit; Feusner, Jamie D

    2013-01-01

    Body dysmorphic disorder (BDD) is characterized by preoccupation with misperceived defects of appearance, causing significant distress and disability. Previous studies suggest abnormalities in information processing characterized by greater local relative to global processing. The purpose of this study was to probe whole-brain and regional white matter network organization in BDD, and to relate this to specific metrics of symptomatology. We acquired diffusion-weighted 34-direction MR images from 14 unmedicated participants with DSM-IV BDD and 16 healthy controls, from which we conducted whole-brain deterministic diffusion tensor imaging tractography. We then constructed white matter structural connectivity matrices to derive whole-brain and regional graph theory metrics, which we compared between groups. Within the BDD group, we additionally correlated these metrics with scores on psychometric measures of BDD symptom severity as well as poor insight/delusionality. The BDD group showed higher whole-brain mean clustering coefficient than controls. Global efficiency negatively correlated with BDD symptom severity. The BDD group demonstrated greater edge betweenness centrality for connections between the anterior temporal lobe and the occipital cortex, and between bilateral occipital poles. This represents the first brain network analysis in BDD. Results suggest disturbances in whole brain structural topological organization in BDD, in addition to correlations between clinical symptoms and network organization. There is also evidence of abnormal connectivity between regions involved in lower-order visual processing and higher-order visual and emotional processing, as well as interhemispheric visual information transfer. These findings may relate to disturbances in information processing found in previous studies. PMID:23322186

  11. Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain

    Science.gov (United States)

    Arbib, Michael A.

    2016-03-01

    We make the case for developing a Computational Comparative Neuroprimatology to inform the analysis of the function and evolution of the human brain. First, we update the mirror system hypothesis on the evolution of the language-ready brain by (i) modeling action and action recognition and opportunistic scheduling of macaque brains to hypothesize the nature of the last common ancestor of macaque and human (LCA-m); and then we (ii) introduce dynamic brain modeling to show how apes could acquire gesture through ontogenetic ritualization, hypothesizing the nature of evolution from LCA-m to the last common ancestor of chimpanzee and human (LCA-c). We then (iii) hypothesize the role of imitation, pantomime, protosign and protospeech in biological and cultural evolution from LCA-c to Homo sapiens with a language-ready brain. Second, we suggest how cultural evolution in Homo sapiens led from protolanguages to full languages with grammar and compositional semantics. Third, we assess the similarities and differences between the dorsal and ventral streams in audition and vision as the basis for presenting and comparing two models of language processing in the human brain: A model of (i) the auditory dorsal and ventral streams in sentence comprehension; and (ii) the visual dorsal and ventral streams in defining ;what language is about; in both production and perception of utterances related to visual scenes provide the basis for (iii) a first step towards a synthesis and a look at challenges for further research.

  12. Brain imaging and networks in restless legs syndrome

    Science.gov (United States)

    Rizzo, Giovanni; Li, Xu; Galantucci, Sebastiano; Filippi, Massimo; Cho, Yong Won

    2018-01-01

    Several studies provide information useful to our understanding of restless legs syndrome (RLS), using various imaging techniques to investigate different aspects putatively involved in the pathophysiology of RLS, although there are discrepancies between these findings. The majority of magnetic resonance imaging (MRI) studies using iron-sensitive sequences supports the presence of a diffuse, but regionally variable low brain-iron content, mainly at the level of the substantia nigra, but there is increasing evidence of reduced iron levels in the thalamus. Positron emission tomography (PET) and single positron emission computed tomography (SPECT) findings mainly support dysfunction of dopaminergic pathways involving not only the nigrostriatal but also mesolimbic pathways. None or variable brain structural or microstructural abnormalities have been reported in RLS patients; reports are slightly more consistent concerning levels of white matter. Most of the reported changes were in regions belonging to sensorimotor and limbic/nociceptive networks. Functional MRI studies have demonstrated activation or connectivity changes in the same networks. The thalamus, which includes different sensorimotor and limbic/nociceptive networks, appears to have lower iron content, metabolic abnormalities, dopaminergic dysfunction, and changes in activation and functional connectivity. Summarizing these findings, the primary change could be the reduction of brain iron content, which leads to dysfunction of mesolimbic and nigrostriatal dopaminergic pathways, and in turn to a dysregulation of limbic and sensorimotor networks. Future studies in RLS should evaluate the actual causal relationship among these findings, better investigate the role of neurotransmitters other than dopamine, focus on brain networks by connectivity analysis, and test the reversibility of the different imaging findings following therapy. PMID:27838239

  13. Construction of Individual Morphological Brain Networks with Multiple Morphometric Features

    Directory of Open Access Journals (Sweden)

    Chunlan Yang

    2017-04-01

    Full Text Available In recent years, researchers have increased attentions to the morphological brain network, which is generally constructed by measuring the mathematical correlation across regions using a certain morphometric feature, such as regional cortical thickness and voxel intensity. However, cerebral structure can be characterized by various factors, such as regional volume, surface area, and curvature. Moreover, most of the morphological brain networks are population-based, which has limitations in the investigations of individual difference and clinical applications. Hence, we have extended previous studies by proposing a novel method for realizing the construction of an individual-based morphological brain network through a combination of multiple morphometric features. In particular, interregional connections are estimated using our newly introduced feature vectors, namely, the Pearson correlation coefficient of the concatenation of seven morphometric features. Experiments were performed on a healthy cohort of 55 subjects (24 males aged from 20 to 29 and 31 females aged from 20 to 28 each scanned twice, and reproducibility was evaluated through test–retest reliability. The robustness of morphometric features was measured firstly to select the more reproducible features to form the connectomes. Then the topological properties were analyzed and compared with previous reports of different modalities. Small-worldness was observed in all the subjects at the range of the entire network sparsity (20–40%, and configurations were comparable with previous findings at the sparsity of 23%. The spatial distributions of the hub were found to be significantly influenced by the individual variances, and the hubs obtained by averaging across subjects and sparsities showed correspondence with previous reports. The intraclass coefficient of graphic properties (clustering coefficient = 0.83, characteristic path length = 0.81, betweenness centrality = 0.78 indicates

  14. Evaluation of the factors influencing brain language laterality in presurgical planning.

    Science.gov (United States)

    Batouli, Seyed Amir Hossein; Hasani, Nafiseh; Gheisari, Sara; Behzad, Ebrahim; Oghabian, Mohammad Ali

    2016-10-01

    Brain lesions cause functional deficits, and one treatment for this condition is lesion resection. In most cases, presurgical planning (PSP) and the information from laterality indices are necessary for maximum preservation of the critical functions after surgery. Language laterality index (LI) is reliably estimated using functional magnetic resonance imaging (fMRI); however, this measure is under the influence of some external factors. In this study, we investigated the influence of a number of factors on language LI, using data from 120 patients (mean age=35.65 (±13.4) years) who underwent fMRI for PSP. Using two proposed language tasks from our previous works, brain left hemisphere was showed to be dominant for the language function, although a higher LI was obtained using the "Word Generation" task, compared to the "Reverse Word Reading". In addition, decline of LIs with age, and lower LI when the lesion invaded brain language area were observed. Meanwhile, gender, lesion side (affected hemisphere), LI calculation strategy, and fMRI analysis Z-values did not statistically show any influences on the LIs. Although fMRI is widely used to estimate language LI, it is shown here that in order to present a reliable language LI and to correctly select the dominant hemisphere of the brain, the influence of external factors should be carefully considered. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

  15. Neuroplasticity as a function of second language learning: anatomical changes in the human brain.

    Science.gov (United States)

    Li, Ping; Legault, Jennifer; Litcofsky, Kaitlyn A

    2014-09-01

    The brain has an extraordinary ability to functionally and physically change or reconfigure its structure in response to environmental stimulus, cognitive demand, or behavioral experience. This property, known as neuroplasticity, has been examined extensively in many domains. But how does neuroplasticity occur in the brain as a function of an individual's experience with a second language? It is not until recently that we have gained some understanding of this question by examining the anatomical changes as well as functional neural patterns that are induced by the learning and use of multiple languages. In this article we review emerging evidence regarding how structural neuroplasticity occurs in the brain as a result of one's bilingual experience. Our review aims at identifying the processes and mechanisms that drive experience-dependent anatomical changes, and integrating structural imaging evidence with current knowledge of functional neural plasticity of language and other cognitive skills. The evidence reviewed so far portrays a picture that is highly consistent with structural neuroplasticity observed for other domains: second language experience-induced brain changes, including increased gray matter (GM) density and white matter (WM) integrity, can be found in children, young adults, and the elderly; can occur rapidly with short-term language learning or training; and are sensitive to age, age of acquisition, proficiency or performance level, language-specific characteristics, and individual differences. We conclude with a theoretical perspective on neuroplasticity in language and bilingualism, and point to future directions for research. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Mild traumatic brain injury: Graph-model characterization of brain networks for episodic memory

    NARCIS (Netherlands)

    Tsirka, V.; Simos, P.G.; Vakis, A.; Kanatsouli, K.; Vourkas, M.; Erimaki, S.; Pachou, E.; Stam, C.J.; Micheloyannis, S.

    2011-01-01

    Episodic memory is among the cognitive functions that can be affected in the acute phase following mild traumatic brain injury (MTBI). The present study used EEG recordings to evaluate global synchronization and network organization of rhythmic activity during the encoding and recognition phases of

  17. Hemispheric language dominance measured by repetitive navigated transcranial magnetic stimulation and postoperative course of language function in brain tumor patients.

    Science.gov (United States)

    Ille, Sebastian; Kulchytska, Nataliia; Sollmann, Nico; Wittig, Regina; Beurskens, Eva; Butenschoen, Vicki M; Ringel, Florian; Vajkoczy, Peter; Meyer, Bernhard; Picht, Thomas; Krieg, Sandro M

    2016-10-01

    The resection of left-sided perisylvian brain lesions harbors the risk of postoperative aphasia. Because it is known that language function can shift between hemispheres in brain tumor patients, the preoperative knowledge of the patient's language dominance could be helpful. We therefore investigated the hemispheric language dominance by repetitive navigated transcranial magnetic stimulation (rTMS) and surgery-related deficits of language function. We pooled the bicentric language mapping data of 80 patients undergoing the resection of left-sided perisylvian brain lesions in our two university neurosurgical departments. We calculated error rates (ERs; ER = errors per stimulations) for both hemispheres and defined the hemispheric dominance ratio (HDR) as the quotient of the left- and right-sided ER (HDR >1= left dominant; HDR language function was evaluated and correlated with the preoperative HDR. Only three of 80 patients (4%) presented with permanent surgery-related aphasia and 24 patients (30%) with transient surgery-related aphasia. The mean HDR (± standard deviation) of patients with new aphasia after five days was significantly higher (1.68±1.07) than the HDR of patients with no new language deficit (1.37±1.08) (p=0.0482). With a predefined cut-off value of 0.5 for HDR, we achieved a sensitivity for predicting new aphasia of 100%. A higher preoperative HDR significantly correlates with an increased risk for transient aphasia. Moreover, the intensive preoperative workup in this study led to a considerably low rate of permanent aphasia. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Disruption of functional networks in dyslexia: A whole-brain, data-driven analysis of connectivity

    Science.gov (United States)

    Finn, Emily S.; Shen, Xilin; Holahan, John M.; Scheinost, Dustin; Lacadie, Cheryl; Papademetris, Xenophon; Shaywitz, Sally E.; Shaywitz, Bennett A.; Constable, R. Todd

    2013-01-01

    Background Functional connectivity analyses of fMRI data are a powerful tool for characterizing brain networks and how they are disrupted in neural disorders. However, many such analyses examine only one or a small number of a priori seed regions. Studies that consider the whole brain frequently rely on anatomic atlases to define network nodes, which may result in mixing distinct activation timecourses within a single node. Here, we improve upon previous methods by using a data-driven brain parcellation to compare connectivity profiles of dyslexic (DYS) versus non-impaired (NI) readers in the first whole-brain functional connectivity analysis of dyslexia. Methods Whole-brain connectivity was assessed in children (n = 75; 43 NI, 32 DYS) and adult (n = 104; 64 NI, 40 DYS) readers. Results Compared to NI readers, DYS readers showed divergent connectivity within the visual pathway and between visual association areas and prefrontal attention areas; increased right-hemisphere connectivity; reduced connectivity in the visual word-form area (part of the left fusiform gyrus specialized for printed words); and persistent connectivity to anterior language regions around the inferior frontal gyrus. Conclusions Together, findings suggest that NI readers are better able to integrate visual information and modulate their attention to visual stimuli, allowing them to recognize words based on their visual properties, while DYS readers recruit altered reading circuits and rely on laborious phonology-based “sounding out” strategies into adulthood. These results deepen our understanding of the neural basis of dyslexia and highlight the importance of synchrony between diverse brain regions for successful reading. PMID:24124929

  19. Energy landscapes of resting-state brain networks

    Directory of Open Access Journals (Sweden)

    Takamitsu eWatanabe

    2014-02-01

    Full Text Available During rest, the human brain performs essential functions such as memory maintenance, which are associated with resting-state brain networks (RSNs including the default-mode network (DMN and frontoparietal network (FPN. Previous studies based on spiking-neuron network models and their reduced models, as well as those based on imaging data, suggest that resting-state network activity can be captured as attractor dynamics, i.e., dynamics of the brain state toward an attractive state and transitions between different attractors. Here, we analyze the energy landscapes of the RSNs by applying the maximum entropy model, or equivalently the Ising spin model, to human RSN data. We use the previously estimated parameter values to define the energy landscape, and the disconnectivity graph method to estimate the number of local energy minima (equivalent to attractors in attractor dynamics, the basin size, and hierarchical relationships among the different local minima. In both of the DMN and FPN, low-energy local minima tended to have large basins. A majority of the network states belonged to a basin of one of a few local minima. Therefore, a small number of local minima constituted the backbone of each RSN. In the DMN, the energy landscape consisted of two groups of low-energy local minima that are separated by a relatively high energy barrier. Within each group, the activity patterns of the local minima were similar, and different minima were connected by relatively low energy barriers. In the FPN, all dominant energy were separated by relatively low energy barriers such that they formed a single coarse-grained global minimum. Our results indicate that multistable attractor dynamics may underlie the DMN, but not the FPN, and assist memory maintenance with different memory states.

  20. Large-Scale Functional Brain Network Reorganization During Taoist Meditation.

    Science.gov (United States)

    Jao, Tun; Li, Chia-Wei; Vértes, Petra E; Wu, Changwei Wesley; Achard, Sophie; Hsieh, Chao-Hsien; Liou, Chien-Hui; Chen, Jyh-Horng; Bullmore, Edward T

    2016-02-01

    Meditation induces a distinct and reversible mental state that provides insights into brain correlates of consciousness. We explored brain network changes related to meditation by graph theoretical analysis of resting-state functional magnetic resonance imaging data. Eighteen Taoist meditators with varying levels of expertise were scanned using a within-subjects counterbalanced design during resting and meditation states. State-related differences in network topology were measured globally and at the level of individual nodes and edges. Although measures of global network topology, such as small-worldness, were unchanged, meditation was characterized by an extensive and expertise-dependent reorganization of the hubs (highly connected nodes) and edges (functional connections). Areas of sensory cortex, especially the bilateral primary visual and auditory cortices, and the bilateral temporopolar areas, which had the highest degree (or connectivity) during the resting state, showed the biggest decrease during meditation. Conversely, bilateral thalamus and components of the default mode network, mainly the bilateral precuneus and posterior cingulate cortex, had low degree in the resting state but increased degree during meditation. Additionally, these changes in nodal degree were accompanied by reorganization of anatomical orientation of the edges. During meditation, long-distance longitudinal (antero-posterior) edges increased proportionally, whereas orthogonal long-distance transverse (right-left) edges connecting bilaterally homologous cortices decreased. Our findings suggest that transient changes in consciousness associated with meditation introduce convergent changes in the topological and spatial properties of brain functional networks, and the anatomical pattern of integration might be as important as the global level of integration when considering the network basis for human consciousness.

  1. An Analysis of Social Network Websites for Language Learning: Implications for Teaching and Learning English as a Second Language

    Science.gov (United States)

    Liu, M.; Abe, K.; Cao, M. W.; Liu, S.; Ok, D. U.; Park, J.; Parrish, C.; Sardegna, V. G.

    2015-01-01

    Although educators are excited about the potential of social network sites for language learning (SNSLL), there is a lack of understanding of how SNSLL can be used to facilitate teaching and learning for English as Second language (ESL) instructors and students. The purpose of this study was to examine the affordances of four selected SNSLL…

  2. Modafinil enhances alerting-related brain activity in attention networks.

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    Ikeda, Yumiko; Funayama, Takuya; Tateno, Amane; Fukayama, Haruhisa; Okubo, Yoshiro; Suzuki, Hidenori

    2017-07-01

    Modafinil is a wake-promoting agent and has been reported to be effective in improving attention in patients with attentional disturbance. However, neural substrates underlying the modafinil effects on attention are not fully understood. We employed a functional magnetic resonance imaging (fMRI) study with the attention network test (ANT) task in healthy adults and examined which networks of attention are mainly affected by modafinil and which neural substrates are responsible for the drug effects. We used a randomized placebo-controlled within-subjects cross-over design. Twenty-three healthy adults participated in two series of an fMRI study, taking either a placebo or modafinil. The participants performed the ANT task, which is designed to measure three distinct attentional networks, alerting, orienting, and executive control, during the fMRI scanning. The effects of modafinil on behavioral performance and regional brain activity were analyzed. We found that modafinil enhanced alerting performance and showed greater alerting network activity in the left middle and inferior occipital gyri as compared with the placebo. The brain activations in the occipital regions were positively correlated with alerting performance. Modafinil enhanced alerting performance and increased activation in the occipital lobe in the alerting network possibly relevant to noradrenergic activity during the ANT task. The present study may provide a rationale for the treatment of patients with distinct symptoms of impaired attention.

  3. Improving the Reliability of Network Metrics in Structural Brain Networks by Integrating Different Network Weighting Strategies into a Single Graph

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    Stavros I. Dimitriadis

    2017-12-01

    Full Text Available Structural brain networks estimated from diffusion MRI (dMRI via tractography have been widely studied in healthy controls and patients with neurological and psychiatric diseases. However, few studies have addressed the reliability of derived network metrics both node-specific and network-wide. Different network weighting strategies (NWS can be adopted to weight the strength of connection between two nodes yielding structural brain networks that are almost fully-weighted. Here, we scanned five healthy participants five times each, using a diffusion-weighted MRI protocol and computed edges between 90 regions of interest (ROI from the Automated Anatomical Labeling (AAL template. The edges were weighted according to nine different methods. We propose a linear combination of these nine NWS into a single graph using an appropriate diffusion distance metric. We refer to the resulting weighted graph as an Integrated Weighted Structural Brain Network (ISWBN. Additionally, we consider a topological filtering scheme that maximizes the information flow in the brain network under the constraint of the overall cost of the surviving connections. We compared each of the nine NWS and the ISWBN based on the improvement of: (a intra-class correlation coefficient (ICC of well-known network metrics, both node-wise and per network level; and (b the recognition accuracy of each subject compared to the remainder of the cohort, as an attempt to access the uniqueness of the structural brain network for each subject, after first applying our proposed topological filtering scheme. Based on a threshold where the network level ICC should be >0.90, our findings revealed that six out of nine NWS lead to unreliable results at the network level, while all nine NWS were unreliable at the node level. In comparison, our proposed ISWBN performed as well as the best performing individual NWS at the network level, and the ICC was higher compared to all individual NWS at the node

  4. The emergence of grammar in a language-ready brain. Comment on "Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain" by Michael A. Arbib

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    Hawkins, John A.

    2016-03-01

    Arbib makes the interesting proposal [3, §1.6] that the first Homo sapiens could have been ;language-ready;, without possessing the kind of rich lexicon, grammar and compositional semantics that we see in the world's languages today. This early language readiness would have consisted of a set of ;protolanguage; abilities, which he enumerates (1-7 in §1.6), supported by brain mechanisms unique to humans. The transition to full ;language; (properties 8-11 in §1.6 and §3) would have required no changes in the genome, he argues, but could have resulted from cultural evolution plus some measure of Baldwinian evolution favoring offspring with greater linguistic skill. The full picture is set out in [1].

  5. Network structure of brain atrophy in de novo Parkinson's disease.

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    Zeighami, Yashar; Ulla, Miguel; Iturria-Medina, Yasser; Dadar, Mahsa; Zhang, Yu; Larcher, Kevin Michel-Herve; Fonov, Vladimir; Evans, Alan C; Collins, D Louis; Dagher, Alain

    2015-09-07

    We mapped the distribution of atrophy in Parkinson's disease (PD) using magnetic resonance imaging (MRI) and clinical data from 232 PD patients and 117 controls from the Parkinson's Progression Markers Initiative. Deformation-based morphometry and independent component analysis identified PD-specific atrophy in the midbrain, basal ganglia, basal forebrain, medial temporal lobe, and discrete cortical regions. The degree of atrophy reflected clinical measures of disease severity. The spatial pattern of atrophy demonstrated overlap with intrinsic networks present in healthy brain, as derived from functional MRI. Moreover, the degree of atrophy in each brain region reflected its functional and anatomical proximity to a presumed disease epicenter in the substantia nigra, compatible with a trans-neuronal spread of the disease. These results support a network-spread mechanism in PD. Finally, the atrophy pattern in PD was also seen in healthy aging, where it also correlated with the loss of striatal dopaminergic innervation.

  6. Hebrew Brain vs. English Brain: Language Modulates the Way It Is Processed

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    Bick, Atira S.; Goelman, Gadi; Frost, Ram

    2011-01-01

    Is language processing universal? How do the specific properties of each language influence the way it is processed? In this study, we compare the neural correlates of morphological processing in Hebrew--a Semitic language with a rich and systematic morphology, to those revealed in English--an Indo-European language with a linear morphology. Using…

  7. Neural Correlates of Unconsciousness in Large-Scale Brain Networks.

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    Mashour, George A; Hudetz, Anthony G

    2018-03-01

    The biological basis of consciousness is one of the most challenging and fundamental questions in 21st century science. A related pursuit aims to identify the neural correlates and causes of unconsciousness. We review current trends in the investigation of physiological, pharmacological, and pathological states of unconsciousness at the level of large-scale functional brain networks. We focus on the roles of brain connectivity, repertoire, graph-theoretical techniques, and neural dynamics in understanding the functional brain disconnections and reduced complexity that appear to characterize these states. Persistent questions in the field, such as distinguishing true correlates, linking neural scales, and understanding differential recovery patterns, are also addressed. Copyright © 2018 Elsevier Ltd. All rights reserved.

  8. Volumetric multimodality neural network for brain tumor segmentation

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    Silvana Castillo, Laura; Alexandra Daza, Laura; Carlos Rivera, Luis; Arbeláez, Pablo

    2017-11-01

    Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an emphasis on the medical field. We present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric data along with information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. Our method is based on DeepMedic, the state of the art in brain lesion segmentation. We develop a new architecture with more convolutional layers, organized in three parallel pathways with different input resolution, and additional fully connected layers. We tested our method over the 2015 BraTS Challenge dataset, reaching an average dice coefficient of 84%, while the standard DeepMedic implementation reached 74%.

  9. Multilayer network of language: A unified framework for structural analysis of linguistic subsystems

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    Martinčić-Ipšić, Sanda; Margan, Domagoj; Meštrović, Ana

    2016-09-01

    Recently, the focus of complex networks' research has shifted from the analysis of isolated properties of a system toward a more realistic modeling of multiple phenomena - multilayer networks. Motivated by the prosperity of multilayer approach in social, transport or trade systems, we introduce the multilayer networks for language. The multilayer network of language is a unified framework for modeling linguistic subsystems and their structural properties enabling the exploration of their mutual interactions. Various aspects of natural language systems can be represented as complex networks, whose vertices depict linguistic units, while links model their relations. The multilayer network of language is defined by three aspects: the network construction principle, the linguistic subsystem and the language of interest. More precisely, we construct a word-level (syntax and co-occurrence) and a subword-level (syllables and graphemes) network layers, from four variations of original text (in the modeled language). The analysis and comparison of layers at the word and subword-levels are employed in order to determine the mechanism of the structural influences between linguistic units and subsystems. The obtained results suggest that there are substantial differences between the networks' structures of different language subsystems, which are hidden during the exploration of an isolated layer. The word-level layers share structural properties regardless of the language (e.g. Croatian or English), while the syllabic subword-level expresses more language dependent structural properties. The preserved weighted overlap quantifies the similarity of word-level layers in weighted and directed networks. Moreover, the analysis of motifs reveals a close topological structure of the syntactic and syllabic layers for both languages. The findings corroborate that the multilayer network framework is a powerful, consistent and systematic approach to model several linguistic subsystems

  10. Language Development and Brain Magnetic Resonance Imaging Characteristics in Preschool Children With Cerebral Palsy.

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    Choi, Ja Young; Choi, Yoon Seong; Park, Eun Sook

    2017-05-24

    The purpose of this study was to investigate characteristics of language development in relation to brain magnetic resonance imaging (MRI) characteristics and the other contributing factors to language development in children with cerebral palsy (CP). The study included 172 children with CP who underwent brain MRI and language assessments between 3 and 7 years of age. The MRI characteristics were categorized as normal, malformation, periventricular white matter lesion (PVWL), deep gray matter lesion, focal infarct, cortical/subcortical lesion, and others. Neurodevelopmental outcomes such as ambulatory status, manual ability, cognitive function, and accompanying impairments were assessed. Both receptive and expressive language development quotients (DQs) were significantly related to PVWL or deep gray matter lesion severity. In multivariable analysis, only cognitive function was significantly related to receptive language development, whereas ambulatory status and cognitive function were significantly associated with expressive language development. More than one third of the children had a language developmental discrepancy between receptive and expressive DQs. Children with cortical/subcortical lesions were at high risk for this discrepancy. Cognitive function is a key factor for both receptive and expressive language development. In children with PVWL or deep gray matter lesion, lesion severity seems to be useful to predict language development.

  11. Dynamic reconfiguration of human brain functional networks through neurofeedback.

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    Haller, Sven; Kopel, Rotem; Jhooti, Permi; Haas, Tanja; Scharnowski, Frank; Lovblad, Karl-Olof; Scheffler, Klaus; Van De Ville, Dimitri

    2013-11-01

    Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e.g., learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. Spatial dependencies between large-scale brain networks.

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    Robert Leech

    Full Text Available Functional neuroimaging reveals both increases (task-positive and decreases (task-negative in neural activation with many tasks. Many studies show a temporal relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a spatial relationship between task positive and negative networks. There are strong spatial similarities between many reported task negative brain networks, termed the default mode network, which is typically assumed to be a spatially fixed network. However, this is not the case. The spatial structure of the DMN varies depending on what specific task is being performed. We test whether there is a fundamental spatial relationship between task positive and negative networks. Specifically, we hypothesize that the distance between task positive and negative voxels is consistent despite different spatial patterns of activation and deactivation evoked by different cognitive tasks. We show significantly reduced variability in the distance between within-condition task positive and task negative voxels than across-condition distances for four different sensory, motor and cognitive tasks--implying that deactivation patterns are spatially dependent on activation patterns (and vice versa, and that both are modulated by specific task demands. We also show a similar relationship between positively and negatively correlated networks from a third 'rest' dataset, in the absence of a specific task. We propose that this spatial relationship may be the macroscopic analogue of microscopic neuronal organization reported in sensory cortical systems, and that this organization may reflect homeostatic plasticity necessary for efficient brain function.

  13. Reverse engineering GTPase programming languages with reconstituted signaling networks.

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    Coyle, Scott M

    2016-07-02

    The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems.

  14. Brain Structural Covariance Network Topology in Remitted Posttraumatic Stress Disorder

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    Delin Sun

    2018-03-01

    Full Text Available Posttraumatic stress disorder (PTSD is a prevalent, chronic disorder with high psychiatric morbidity; however, a substantial portion of affected individuals experience remission after onset. Alterations in brain network topology derived from cortical thickness correlations are associated with PTSD, but the effects of remitted symptoms on network topology remain essentially unexplored. In this cross-sectional study, US military veterans (N = 317 were partitioned into three diagnostic groups, current PTSD (CURR-PTSD, N = 101, remitted PTSD with lifetime but no current PTSD (REMIT-PTSD, N = 35, and trauma-exposed controls (CONTROL, n = 181. Cortical thickness was assessed for 148 cortical regions (nodes and suprathreshold interregional partial correlations across subjects constituted connections (edges in each group. Four centrality measures were compared with characterize between-group differences. The REMIT-PTSD and CONTROL groups showed greater centrality in left frontal pole than the CURR-PTSD group. The REMIT-PTSD group showed greater centrality in right subcallosal gyrus than the other two groups. Both REMIT-PTSD and CURR-PTSD groups showed greater centrality in right superior frontal sulcus than CONTROL group. The centrality in right subcallosal gyrus, left frontal pole, and right superior frontal sulcus may play a role in remission, current symptoms, and PTSD history, respectively. The network centrality changes in critical brain regions and structural networks are associated with remitted PTSD, which typically coincides with enhanced functional behaviors, better emotion regulation, and improved cognitive processing. These brain regions and associated networks may be candidates for developing novel therapies for PTSD. Longitudinal work is needed to characterize vulnerability to chronic PTSD, and resilience to unremitting PTSD.

  15. Abnormal Functional Lateralization and Activity of Language Brain Areas in Typical Specific Language Impairment (Developmental Dysphasia)

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    de Guibert, Clement; Maumet, Camille; Jannin, Pierre; Ferre, Jean-Christophe; Treguier, Catherine; Barillot, Christian; Le Rumeur, Elisabeth; Allaire, Catherine; Biraben, Arnaud

    2011-01-01

    Atypical functional lateralization and specialization for language have been proposed to account for developmental language disorders, yet results from functional neuroimaging studies are sparse and inconsistent. This functional magnetic resonance imaging study compared children with a specific subtype of specific language impairment affecting…

  16. Attention to language: novel MEG paradigm for registering involuntary language processing in the brain.

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    Shtyrov, Yury; Smith, Marie L; Horner, Aidan J; Henson, Richard; Nathan, Pradeep J; Bullmore, Edward T; Pulvermüller, Friedemann

    2012-09-01

    Previous research indicates that, under explicit instructions to listen to spoken stimuli or in speech-oriented behavioural tasks, the brain's responses to senseless pseudowords are larger than those to meaningful words; the reverse is true in non-attended conditions. These differential responses could be used as a tool to trace linguistic processes in the brain and their interaction with attention. However, as previous studies relied on explicit instructions to attend or ignore the stimuli, a technique for automatic attention modulation (i.e., not dependent on explicit instruction) would be more advantageous, especially when cooperation with instructions may not be guaranteed (e.g., neurological patients, children etc). Here we present a novel paradigm in which the stimulus context automatically draws attention to speech. In a non-attend passive auditory oddball sequence, rare words and pseudowords were presented among frequent non-speech tones of variable frequency and length. The low percentage of spoken stimuli guarantees an involuntary attention switch to them. The speech stimuli, in turn, could be disambiguated as words or pseudowords only in their end, at the last phoneme, after the attention switch would have already occurred. Our results confirmed that this paradigm can indeed be used to induce automatic shifts of attention to spoken input. At ~250ms after the stimulus onset, a P3a-like neuromagnetic deflection was registered to spoken (but not tone) stimuli indicating an involuntary attention shift. Later, after the word-pseudoword divergence point, we found a larger oddball response to pseudowords than words, best explained by neural processes of lexical search facilitated through increased attention. Furthermore, we demonstrate a breakdown of this orderly pattern of neurocognitive processes as a result of sleep deprivation. The new paradigm may thus be an efficient way to assess language comprehension processes and their dynamic interaction with those

  17. Network Statistical Models for Language Learning Contexts: Exponential Random Graph Models and Willingness to Communicate

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    Gallagher, H. Colin; Robins, Garry

    2015-01-01

    As part of the shift within second language acquisition (SLA) research toward complex systems thinking, researchers have called for investigations of social network structure. One strand of social network analysis yet to receive attention in SLA is network statistical models, whereby networks are explained in terms of smaller substructures of…

  18. Large-scale brain networks in affective and social neuroscience: Towards an integrative functional architecture of the brain

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    Barrett, Lisa Feldman; Satpute, Ajay

    2013-01-01

    Understanding how a human brain creates a human mind ultimately depends on mapping psychological categories and concepts to physical measurements of neural response. Although it has long been assumed that emotional, social, and cognitive phenomena are realized in the operations of separate brain regions or brain networks, we demonstrate that it is possible to understand the body of neuroimaging evidence using a framework that relies on domain general, distributed structure-function mappings. We review current research in affective and social neuroscience and argue that the emerging science of large-scale intrinsic brain networks provides a coherent framework for a domain-general functional architecture of the human brain. PMID:23352202

  19. Spectral Signatures of Reorganised Brain Networks in Disorders of Consciousness

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    Chennu, Srivas; Finoia, Paola; Kamau, Evelyn; Allanson, Judith; Williams, Guy B.; Monti, Martin M.; Noreika, Valdas; Arnatkeviciute, Aurina; Canales-Johnson, Andrés; Olivares, Francisco; Cabezas-Soto, Daniela; Menon, David K.; Pickard, John D.; Owen, Adrian M.; Bekinschtein, Tristan A.

    2014-01-01

    Theoretical advances in the science of consciousness have proposed that it is concomitant with balanced cortical integration and differentiation, enabled by efficient networks of information transfer across multiple scales. Here, we apply graph theory to compare key signatures of such networks in high-density electroencephalographic data from 32 patients with chronic disorders of consciousness, against normative data from healthy controls. Based on connectivity within canonical frequency bands, we found that patient networks had reduced local and global efficiency, and fewer hubs in the alpha band. We devised a novel topographical metric, termed modular span, which showed that the alpha network modules in patients were also spatially circumscribed, lacking the structured long-distance interactions commonly observed in the healthy controls. Importantly however, these differences between graph-theoretic metrics were partially reversed in delta and theta band networks, which were also significantly more similar to each other in patients than controls. Going further, we found that metrics of alpha network efficiency also correlated with the degree of behavioural awareness. Intriguingly, some patients in behaviourally unresponsive vegetative states who demonstrated evidence of covert awareness with functional neuroimaging stood out from this trend: they had alpha networks that were remarkably well preserved and similar to those observed in the controls. Taken together, our findings inform current understanding of disorders of consciousness by highlighting the distinctive brain networks that characterise them. In the significant minority of vegetative patients who follow commands in neuroimaging tests, they point to putative network mechanisms that could support cognitive function and consciousness despite profound behavioural impairment. PMID:25329398

  20. Social Rewards and Social Networks in the Human Brain.

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    Fareri, Dominic S; Delgado, Mauricio R

    2014-08-01

    The rapid development of social media and social networking sites in human society within the past decade has brought about an increased focus on the value of social relationships and being connected with others. Research suggests that we pursue socially valued or rewarding outcomes-approval, acceptance, reciprocity-as a means toward learning about others and fulfilling social needs of forming meaningful relationships. Focusing largely on recent advances in the human neuroimaging literature, we review findings highlighting the neural circuitry and processes that underlie pursuit of valued rewarding outcomes across non-social and social domains. We additionally discuss emerging human neuroimaging evidence supporting the idea that social rewards provide a gateway to establishing relationships and forming social networks. Characterizing the link between social network, brain, and behavior can potentially identify contributing factors to maladaptive influences on decision making within social situations. © The Author(s) 2014.

  1. Using Social Networking Sites as a Platform for Second Language Instruction

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    Prichard, Caleb

    2013-01-01

    Social networking sites (SNSs) are increasingly used to communicate and to maintain relationships with people around the globe, and their usage has certainly led to incidental language gains for second language (L2) users. Language instructors are just beginning to utilize SNS sites to manage their courses or to have students practice language…

  2. Paradoxes of Social Networking in a Structured Web 2.0 Language Learning Community

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    Loiseau, Mathieu; Zourou, Katerina

    2012-01-01

    This paper critically inquires into social networking as a set of mechanisms and associated practices developed in a structured Web 2.0 language learning community. This type of community can be roughly described as learning spaces featuring (more or less) structured language learning resources displaying at least some notions of language learning…

  3. The Bilingual Brain: Human Evolution and Second Language Acquisition

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    L. Kirk Hagen

    2008-01-01

    Full Text Available For the past half-century, psycholinguistic research has concerned itself with two mysteries of human cognition: (1 that children universally acquire a highly abstract, computationally complex set of linguistic rules rapidly and effortlessly, and (2 that second language acquisition (SLA among adults is, conversely, slow, laborious, highly variable, and virtually never results in native fluency. We now have a decent, if approximate, understanding of the biological foundations of first language acquisition, thanks in large part to Lenneberg's (1964, 1984 seminal work on the critical period hypothesis. More recently, the elements of a promising theory of language and evolution have emerged as well (see e.g. Bickerton, 1981, 1990; Leiberman, 1984, 1987. I argue here that the empirical foundations of an evolutionary theory of language are now solid enough to support an account of bilingualism and adult SLA as well. Specifically, I will show that evidence from the environment of evolutionary adaptation of paleolithic humans suggests that for our nomadic ancestors, the ability to master a language early in life was an eminently useful adaptation. However, the ability to acquire another language in adulthood was not, and consequently was not selected for propagation.

  4. Brain Structural Networks Associated with Intelligence and Visuomotor Ability.

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    Yoon, Youngwoo Bryan; Shin, Won-Gyo; Lee, Tae Young; Hur, Ji-Won; Cho, Kang Ik K; Sohn, William Seunghyun; Kim, Seung-Goo; Lee, Kwang-Hyuk; Kwon, Jun Soo

    2017-05-19

    Increasing evidence indicates that multiple structures in the brain are associated with intelligence and cognitive function at the network level. The association between the grey matter (GM) structural network and intelligence and cognition is not well understood. We applied a multivariate approach to identify the pattern of GM and link the structural network to intelligence and cognitive functions. Structural magnetic resonance imaging was acquired from 92 healthy individuals. Source-based morphometry analysis was applied to the imaging data to extract GM structural covariance. We assessed the intelligence, verbal fluency, processing speed, and executive functioning of the participants and further investigated the correlations of the GM structural networks with intelligence and cognitive functions. Six GM structural networks were identified. The cerebello-parietal component and the frontal component were significantly associated with intelligence. The parietal and frontal regions were each distinctively associated with intelligence by maintaining structural networks with the cerebellum and the temporal region, respectively. The cerebellar component was associated with visuomotor ability. Our results support the parieto-frontal integration theory of intelligence by demonstrating how each core region for intelligence works in concert with other regions. In addition, we revealed how the cerebellum is associated with intelligence and cognitive functions.

  5. The human infant brain: A neural architecture able to learn language.

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    Dehaene-Lambertz, Ghislaine

    2017-02-01

    To understand the type of neural computations that may explain how human infants acquire their native language in only a few months, the study of their neural architecture is necessary. The development of brain imaging techniques has opened the possibilities of studying human infants without discomfort, and although these studies are still sparse, several characteristics are noticeable in the human infant's brain: first, parallel and hierarchical processing pathways are observed before intense exposure to speech with an efficient temporal coding in the left hemisphere and, second, frontal regions are involved from the start in infants' cognition. These observations are certainly not sufficient to explain language acquisition but illustrate a new approach that relies on a better description of infants' brain activity during linguistic tasks, which is compared to results in animals and human adults to clarify the neural bases of language in humans.

  6. Functional brain networks develop from a "local to distributed" organization.

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    Damien A Fair

    2009-05-01

    Full Text Available The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI, graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward 'segregation' (a general decrease in correlation strength between regions close in anatomical space and 'integration' (an increased correlation strength between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more "distributed" architecture in young adults. We argue that this "local to distributed" developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths are similar in child and adult graphs, with both showing "small-world"-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults

  7. Language exposure induced neuroplasticity in the bilingual brain: a follow-up fMRI study.

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    Tu, Liu; Wang, Junjing; Abutalebi, Jubin; Jiang, Bo; Pan, Ximin; Li, Meng; Gao, Wei; Yang, Yuchen; Liang, Bishan; Lu, Zhi; Huang, Ruiwang

    2015-03-01

    Although several studies have shown that language exposure crucially influence the cerebral representation of bilinguals, the effects of short-term change of language exposure in daily life upon language control areas in bilinguals are less known. To explore this issue, we employed follow-up fMRI to investigate whether differential exposure induces neuroplastic changes in the language control network in high-proficient Cantonese (L1)-Mandarin (L2) early bilinguals. The same 10 subjects underwent twice BOLD-fMRI scans while performing a silent narration task which corresponded to two different language exposure conditions, CON-1 (L1/L2 usage percentage, 50%:50%) and CON-2 (L1/L2 usage percentage, 90%:10%). We report a strong effect of language exposure in areas related to language control for the less exposed language. Interestingly, these significant effects were present after only a 30-day period of differential language exposure. In detail, we reached the following results: (1) the interaction effect of language and language exposure condition was found significantly in the left pars opercularis (BA 44) and marginally in the left MFG (BA 9); (2) in CON-2, increases of activation values in L2 were found significantly in bilateral BA 46 and BA 9, in the left BA44, and marginally in the left caudate; and (3) in CON-2, we found a significant negative correlation between language exposure to L2 and the BOLD activation value specifically in the left ACC. These findings strongly support the hypothesis that even short periods of differential exposure to a given language may induce significant neuroplastic changes in areas responsible for language control. The language which a bilingual is less exposed to and is also less used will be in need of increased mental control as shown by the increased activity of language control areas. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

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    Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

    2017-12-01

    State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with

  9. Brain hubs in lesion models: Predicting functional network topology with lesion patterns in patients.

    Science.gov (United States)

    Yuan, Binke; Fang, Yuxing; Han, Zaizhu; Song, Luping; He, Yong; Bi, Yanchao

    2017-12-20

    Various important topological properties of healthy brain connectome have recently been identified. However, the manner in which brain lesion changes the functional network topology is unknown. We examined how critical specific brain areas are in the maintenance of network topology using multivariate support vector regression analysis on brain structural and resting-state functional imaging data in 96 patients with brain damages. Patients' cortical lesion distribution patterns could significantly predict the functional network topology and a set of regions with significant weights in the prediction models were identified as "lesion hubs". Intriguingly, we found two different types of lesion hubs, whose lesions associated with changes of network topology towards relatively different directions, being either more integrated (global) or more segregated (local), and correspond to hubs identified in healthy functional network in complex manners. Our results pose further important questions about the potential dynamics of the functional brain network after brain damage.

  10. [Reconstruction method of language pathways in the preoperative planning of brain tumor surgery].

    Science.gov (United States)

    Yan, Jing; Lu, Junfeng; Cheng, Jingliang; Wu, Jinsong; Zhang, Jie; Wang, Chaoyan; Nie, Yunfei; Pang, Beibei; Liu, Xianzhi

    2015-05-01

    To propose a clinically practical and simple fiber tracking method for language pathways, and to explore its feasibility in preoperative planning for brain tumors adjacent to the language cortex. Diffusion tensor imaging was examined in 18 healthy subjects and 13 patients with brain tumors adjacent to the language cortex between December 2013 and June 2014. The associated fibers of language pathways were reconstructed using a commercial software (Syngo workstation). Firstly, the feasibility of fiber tracking method for language pathways in healthy subjects were studied, and then its application was assessed in patients with brain tumors. The anatomic relationship between tumors and the associated fibers was analyzed. By selecting appropriate regions of interest, the associated fibers in the dorsal pathways (superior longitudinal fasciculus/arcuate fasciculus, including both direct and indirect pathways) and ventral pathways (uncinate fasciculus, middle longitudinal fasciculus, inferior longitudinal fasciculus and inferiorfronto-occipital fasciculus) were reconstructed in all 18 healthy subjects. In patients with brain tumors, the relationship between the tumors and adjacent associated fibers were divided into two types: adjacent associated fibers could be displaced or separated, and involved the superior longitudinal fasciculus/arcuate fasciculus (n=6), middle longitudinal fasciculus (n=4), uncinate fasciculus (n=3), inferior longitudinal fasciculus (n=3) and inferiorfronto-occipital fasciculus (n=2); alternatively, the adjacent associated fibers were infiltrated or destroyed, and involved the inferiorfronto-occipital fasciculus (n=10), uncinate fasciculus (n=8), middle longitudinal fasciculus (n=5), inferior longitudinal fasciculus (n=4) and superior longitudinal fasciculus/arcuate fasciculus (n=3). The associated fibers of language pathways could be visualized rapidly and in real-time by fiber tracking technology based on diffusion tensor imaging. This is

  11. Impact of second-language experience in infancy: brain measures of first- and second-language speech perception.

    Science.gov (United States)

    Conboy, Barbara T; Kuhl, Patricia K

    2011-03-01

    Language experience 'narrows' speech perception by the end of infants' first year, reducing discrimination of non-native phoneme contrasts while improving native-contrast discrimination. Previous research showed that declines in non-native discrimination were reversed by second-language experience provided at 9-10 months, but it is not known whether second-language experience affects first-language speech sound processing. Using event-related potentials (ERPs), we examined learning-related changes in brain activity to Spanish and English phoneme contrasts in monolingual English-learning infants pre- and post-exposure to Spanish from 9.5-10.5 months of age. Infants showed a significant discriminatory ERP response to the Spanish contrast at 11 months (post-exposure), but not at 9 months (pre-exposure). The English contrast elicited an earlier discriminatory response at 11 months than at 9 months, suggesting improvement in native-language processing. The results show that infants rapidly encode new phonetic information, and that improvement in native speech processing can occur during second-language learning in infancy.

  12. The "Globularization Hypothesis" of the Language-ready Brain as a Developmental Frame for Prosodic Bootstrapping Theories of Language Acquisition.

    Science.gov (United States)

    Irurtzun, Aritz

    2015-01-01

    In recent research (Boeckx and Benítez-Burraco, 2014a,b) have advanced the hypothesis that our species-specific language-ready brain should be understood as the outcome of developmental changes that occurred in our species after the split from Neanderthals-Denisovans, which resulted in a more globular braincase configuration in comparison to our closest relatives, who had elongated endocasts. According to these authors, the development of a globular brain is an essential ingredient for the language faculty and in particular, it is the centrality occupied by the thalamus in a globular brain that allows its modulatory or regulatory role, essential for syntactico-semantic computations. Their hypothesis is that the syntactico-semantic capacities arise in humans as a consequence of a process of globularization, which significantly takes place postnatally (cf. Neubauer et al., 2010). In this paper, I show that Boeckx and Benítez-Burraco's hypothesis makes an interesting developmental prediction regarding the path of language acquisition: it teases apart the onset of phonological acquisition and the onset of syntactic acquisition (the latter starting significantly later, after globularization). I argue that this hypothesis provides a developmental rationale for the prosodic bootstrapping hypothesis of language acquisition (cf. i.a. Gleitman and Wanner, 1982; Mehler et al., 1988, et seq.; Gervain and Werker, 2013), which claim that prosodic cues are employed for syntactic parsing. The literature converges in the observation that a large amount of such prosodic cues (in particular, rhythmic cues) are already acquired before the completion of the globularization phase, which paves the way for the premises of the prosodic bootstrapping hypothesis, allowing babies to have a rich knowledge of the prosody of their target language before they can start parsing the primary linguistic data syntactically.

  13. The globularization hypothesis of the language-ready brain as a developmental frame for prosodic bootstrapping theories of language acquisition

    Directory of Open Access Journals (Sweden)

    Aritz eIrurtzun

    2015-12-01

    Full Text Available In recent research Boeckx & Benítez-Burraco (2014a,b have advanced the hypothesis that our species-specific language-ready brain should be understood as the outcome of developmental changes that occurred in our species after the split from Neanderthals-Denisovans, which resulted in a more globular braincase configuration in comparison to our closest relatives, who had elongated endocasts. According to these authors, the development of a globular brain is an essential ingredient for the language faculty and in particular, it is the centrality occupied by the thalamus in a globular brain that allows its modulatory or regulatory role, essential for syntactico-semantic computations. Their hypothesis is that the syntactico-semantic capacities arise in humans as a consequence of a process of globularization, which significantly takes place postnatally (cf. Neubauer et al. (2010. In this paper, I show that Boeckx & Benítez-Burraco’s hypothesis makes an interesting developmental prediction regarding the path of language acquisition: it teases apart the onset of phonological acquisition and the onset of syntactic acquisition (the latter starting significantly later, after globularization. I argue that this hypothesis provides a developmental rationale for the prosodic bootstrapping hypothesis of language acquisition (cf. i.a. Gleitman & Wanner (1982; Mehler et al. (1988, et seq.; Gervain & Werker (2013, which claim that prosodic cues are employed for syntactic parsing. The literature converges in the observation that a large amount of such prosodic cues (in particular, rhythmic cues are already acquired before the completion of the globularization phase, which paves the way for the premises of prosodic bootstrapping hypothesis, allowing babies to have a rich knowledge of the prosody of their target language before they can start parsing the primary linguistic data syntactically.

  14. Network Analysis of Resting State EEG in the Developing Young Brain: Structure Comes With Maturation

    NARCIS (Netherlands)

    Boersma, M.; Smit, D.J.A.; de Bie, H.M.A.; van Baal, G.C.M.; Boomsma, D.I.; de Geus, E.J.C.; Delemarre-van de Waal, H.A.; Stam, C.J.

    2011-01-01

    During childhood, brain structure and function changes substantially. Recently, graph theory has been introduced to model connectivity in the brain. Small-world networks, such as the brain, combine optimal properties of both ordered and random networks, i.e., high clustering and short path lengths.

  15. Why network neuroscience? Compelling evidence and current frontiers. Comment on “Understanding brain networks and brain organization” by Luiz Pessoa

    Science.gov (United States)

    Muldoon, Sarah Feldt; Bassett, Danielle S.

    2014-09-01

    The recent application of network theory to neuroscience has brought new insights into understanding the relationship between brain structure and function [1]. As Pessoa describes in his extensive review [2], the organization of the brain can be viewed as a complex system of connected components that interact at many scales [3], both in the underlying structural architecture and through temporal functional relationships. Importantly, he emphasizes that we must shed the view that a specific brain region can be tied to a specific function and instead view the brain as a dynamic and evolving network in which overlapping sub-networks of brain regions work together to produce different functions. In fact, the complexity of these evolving interactions is now driving the future of network science [4], as efforts focus on developing novel metrics to capture the dynamic essence of these interconnected networks.

  16. How does language change as a lexical network? An investigation based on written Chinese word co-occurrence networks

    Science.gov (United States)

    Chen, Heng; Chen, Xinying

    2018-01-01

    Language is a complex adaptive system, but how does it change? For investigating this process, four diachronic Chinese word co-occurrence networks have been built based on texts that were written during the last 2,000 years. By comparing the network indicators that are associated with the hierarchical features in language networks, we learn that the hierarchy of Chinese lexical networks has indeed evolved over time at three different levels. The connections of words at the micro level are continually weakening; the number of words in the meso-level communities has increased significantly; and the network is expanding at the macro level. This means that more and more words tend to be connected to medium-central words and form different communities. Meanwhile, fewer high-central words link these communities into a highly efficient small-world network. Understanding this process may be crucial for understanding the increasing structural complexity of the language system. PMID:29489837

  17. MULTIPLE INTELLIGENCE THEORY AND FOREIGN LANGUAGE LEARNING:A BRAIN-BASED PERSPECTIVE

    Directory of Open Access Journals (Sweden)

    Jane Arnold

    2004-06-01

    Full Text Available Gardner's Multiple Intelligences theory is presented as a cognitive perspective on intelligence which has profound implications for education in general. More specifically, it has led to the application of eight of these frames to language teaching and learning. In this chapter, we will argue in favour of the application of MIT to the EFL classroom, using as support some of the major insights for language teaching from brain science.

  18. A brain network processing the age of faces.

    Directory of Open Access Journals (Sweden)

    György A Homola

    Full Text Available Age is one of the most salient aspects in faces and of fundamental cognitive and social relevance. Although face processing has been studied extensively, brain regions responsive to age have yet to be localized. Using evocative face morphs and fMRI, we segregate two areas extending beyond the previously established face-sensitive core network, centered on the inferior temporal sulci and angular gyri bilaterally, both of which process changes of facial age. By means of probabilistic tractography, we compare their patterns of functional activation and structural connectivity. The ventral portion of Wernicke's understudied perpendicular association fasciculus is shown to interconnect the two areas, and activation within these clusters is related to the probability of fiber connectivity between them. In addition, post-hoc age-rating competence is found to be associated with high response magnitudes in the left angular gyrus. Our results provide the first evidence that facial age has a distinct representation pattern in the posterior human brain. We propose that particular face-sensitive nodes interact with additional object-unselective quantification modules to obtain individual estimates of facial age. This brain network processing the age of faces differs from the cortical areas that have previously been linked to less developmental but instantly changeable face aspects. Our probabilistic method of associating activations with connectivity patterns reveals an exemplary link that can be used to further study, assess and quantify structure-function relationships.

  19. Dynamic reorganization of intrinsic functional networks in the mouse brain.

    Science.gov (United States)

    Grandjean, Joanes; Preti, Maria Giulia; Bolton, Thomas A W; Buerge, Michaela; Seifritz, Erich; Pryce, Christopher R; Van De Ville, Dimitri; Rudin, Markus

    2017-05-15

    Functional connectivity (FC) derived from resting-state functional magnetic resonance imaging (rs-fMRI) allows for the integrative study of neuronal processes at a macroscopic level. The majority of studies to date have assumed stationary interactions between brain regions, without considering the dynamic aspects of network organization. Only recently has the latter received increased attention, predominantly in human studies. Applying dynamic FC (dFC) analysis to mice is attractive given the relative simplicity of the mouse brain and the possibility to explore mechanisms underlying network dynamics using pharmacological, environmental or genetic interventions. Therefore, we have evaluated the feasibility and research potential of mouse dFC using the interventions of social stress or anesthesia duration as two case-study examples. By combining a sliding-window correlation approach with dictionary learning, several dynamic functional states (dFS) with a complex organization were identified, exhibiting highly dynamic inter- and intra-modular interactions. Each dFS displayed a high degree of reproducibility upon changes in analytical parameters and across datasets. They fluctuated at different degrees as a function of anesthetic depth, and were sensitive indicators of pathology as shown for the chronic psychosocial stress mouse model of depression. Dynamic functional states are proposed to make a major contribution to information integration and processing in the healthy and diseased brain. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Age of language learning shapes brain structure: a cortical thickness study of bilingual and monolingual individuals.

    Science.gov (United States)

    Klein, Denise; Mok, Kelvin; Chen, Jen-Kai; Watkins, Kate E

    2014-04-01

    We examined the effects of learning a second language (L2) on brain structure. Cortical thickness was measured in the MRI datasets of 22 monolinguals and 66 bilinguals. Some bilingual subjects had learned both languages simultaneously (0-3 years) while some had learned their L2 after achieving proficiency in their first language during either early (4-7 years) or late childhood (8-13 years). Later acquisition of L2 was associated with significantly thicker cortex in the left inferior frontal gyrus (IFG) and thinner cortex in the right IFG. These effects were seen in the group comparisons of monolinguals, simultaneous bilinguals and early and late bilinguals. Within the bilingual group, significant correlations between age of acquisition of L2 and cortical thickness were seen in the same regions: cortical thickness correlated with age of acquisition positively in the left IFG and negatively in the right IFG. Interestingly, the monolinguals and simultaneous bilinguals did not differ in cortical thickness in any region. Our results show that learning a second language after gaining proficiency in the first language modifies brain structure in an age-dependent manner whereas simultaneous acquisition of two languages has no additional effect on brain development. Copyright © 2013 Elsevier Inc. All rights reserved.

  1. Two Languages in One Brain: Recent Work in Neurolinguistics and Its Implications for Second Language Learning.

    Science.gov (United States)

    Soudek, Lev I.

    1981-01-01

    Briefly outlines progress in neurolinguistics including Broca's aphasia, multilingual aphasiacs, lateralization, and localization as possible explanations for problem of adult foreign language accent. (BK)

  2. Electrical brain responses in language-impaired children reveal grammar-specific deficits.

    Directory of Open Access Journals (Sweden)

    Elisabeth Fonteneau

    2008-03-01

    Full Text Available Scientific and public fascination with human language have included intensive scrutiny of language disorders as a new window onto the biological foundations of language and its evolutionary origins. Specific language impairment (SLI, which affects over 7% of children, is one such disorder. SLI has received robust scientific attention, in part because of its recent linkage to a specific gene and loci on chromosomes and in part because of the prevailing question regarding the scope of its language impairment: Does the disorder impact the general ability to segment and process language or a specific ability to compute grammar? Here we provide novel electrophysiological data showing a domain-specific deficit within the grammar of language that has been hitherto undetectable through behavioural data alone.We presented participants with Grammatical(G-SLI, age-matched controls, and younger child and adult controls, with questions containing syntactic violations and sentences containing semantic violations. Electrophysiological brain responses revealed a selective impairment to only neural circuitry that is specific to grammatical processing in G-SLI. Furthermore, the participants with G-SLI appeared to be partially compensating for their syntactic deficit by using neural circuitry associated with semantic processing and all non-grammar-specific and low-level auditory neural responses were normal.The findings indicate that grammatical neural circuitry underlying language is a developmentally unique system in the functional architecture of the brain, and this complex higher cognitive system can be selectively impaired. The findings advance fundamental understanding about how cognitive systems develop and all human language is represented and processed in the brain.

  3. Brain Networks Subserving Emotion Regulation and Adaptation after Mild Traumatic Brain Injury.

    Science.gov (United States)

    van der Horn, Harm J; Liemburg, Edith J; Aleman, André; Spikman, Jacoba M; van der Naalt, Joukje

    2016-01-01

    The majority of patients with traumatic brain injury (TBI) sustain a mild injury (mTBI). One out of 4 patients experiences persistent complaints, despite their often normal neuropsychological test results and the absence of structural brain damage on conventional neuroimaging. Susceptibility to develop persistent complaints is thought to be affected by interindividual differences in adaptation, which can also be influenced by preinjury psychological factors. Coping is a key construct of adaptation and refers to strategies to deal with new situations and serious life events. An important element of coping is the ability to regulate emotions and stress. The prefrontal cortex is a crucial area in this regulation process, given that it exerts a top-down influence on the amygdala and other subcortical structures involved in emotion processing. However, little is known about the role of the prefrontal cortex and associated brain networks in emotion regulation and adaptation post-mTBI. Especially, the influence of prefrontal dysfunction on development of persistent postconcussive complaints is poorly understood. In this article, we aim to integrate findings from functional and structural MRI studies on this topic. Alterations within the default mode, executive and salience network have been found in relation to complaints post-mTBI. Dysfunction of the medial prefrontal cortex may impair network dynamics for emotion regulation and adaptation post-mTBI, resulting in persistent post-concussive complaints.

  4. Hallucination- and speech-specific hypercoupling in frontotemporal auditory and language networks in schizophrenia using combined task-based fMRI data: An fBIRN study.

    Science.gov (United States)

    Lavigne, Katie M; Woodward, Todd S

    2017-12-21

    Hypercoupling of activity in speech-perception-specific brain networks has been proposed to play a role in the generation of auditory-verbal hallucinations (AVHs) in schizophrenia; however, it is unclear whether this hypercoupling extends to nonverbal auditory perception. We investigated this by comparing schizophrenia patients with and without AVHs, and healthy controls, on task-based functional magnetic resonance imaging (fMRI) data combining verbal speech perception (SP), inner verbal thought generation (VTG), and nonverbal auditory oddball detection (AO). Data from two previously published fMRI studies were simultaneously analyzed using group constrained principal component analysis for fMRI (group fMRI-CPCA), which allowed for comparison of task-related functional brain networks across groups and tasks while holding the brain networks under study constant, leading to determination of the degree to which networks are common to verbal and nonverbal perception conditions, and which show coordinated hyperactivity in hallucinations. Three functional brain networks emerged: (a) auditory-motor, (b) language processing, and (c) default-mode (DMN) networks. Combining the AO and sentence tasks allowed the auditory-motor and language networks to separately emerge, whereas they were aggregated when individual tasks were analyzed. AVH patients showed greater coordinated activity (deactivity for DMN regions) than non-AVH patients during SP in all networks, but this did not extend to VTG or AO. This suggests that the hypercoupling in AVH patients in speech-perception-related brain networks is specific to perceived speech, and does not extend to perceived nonspeech or inner verbal thought generation. © 2017 Wiley Periodicals, Inc.

  5. Sigmund Freud-early network theories of the brain.

    Science.gov (United States)

    Surbeck, Werner; Killeen, Tim; Vetter, Johannes; Hildebrandt, Gerhard

    2018-03-27

    Since the early days of modern neuroscience, psychological models of brain function have been a key component in the development of new knowledge. These models aim to provide a framework that allows the integration of discoveries derived from the fundamental disciplines of neuroscience, including anatomy and physiology, as well as clinical neurology and psychiatry. During the initial stages of his career, Sigmund Freud (1856-1939), became actively involved in these nascent fields with a burgeoning interest in functional neuroanatomy. In contrast to his contemporaries, Freud was convinced that cognition could not be localised to separate modules and that the brain processes cognition not in a merely serial manner but in a parallel and dynamic fashion-anticipating fundamental aspects of current network theories of brain function. This article aims to shed light on Freud's seminal, yet oft-overlooked, early work on functional neuroanatomy and his reasons for finally abandoning the conventional neuroscientific "brain-based" reference frame in order to conceptualise the mind from a purely psychological perspective.

  6. Quantifying Uncertainty in Brain Network Measures using Bayesian Connectomics

    Directory of Open Access Journals (Sweden)

    Ronald Johannes Janssen

    2014-10-01

    Full Text Available The wiring diagram of the human brain can be described in terms of graph measures that characterize structural regularities. These measures require an estimate of whole-brain structural connectivity for which one may resort to deterministic or thresholded probabilistic streamlining procedures. While these procedures have provided important insights about the characteristics of human brain networks, they ultimately rely on unwarranted assumptions such as those of noise-free data or the use of an arbitrary threshold. Therefore, resulting structural connectivity estimates as well as derived graph measures fail to fully take into account the inherent uncertainty in the structural estimate.In this paper, we illustrate an easy way of obtaining posterior distributions over graph metrics using Bayesian inference. It is shown that this posterior distribution can be used to quantify uncertainty about graph-theoretical measures at the single subject level, thereby providing a more nuanced view of the graph-theoretical properties of human brain connectivity. We refer to this model-based approach to connectivity analysis as Bayesian connectomics.

  7. BrainCrafter: An investigation into human-based neural network engineering

    DEFF Research Database (Denmark)

    Piskur, J.; Greve, P.; Togelius, J.

    2015-01-01

    This paper presents the online application Brain-Crafter, in which users can manually build artificial neural networks (ANNs) to control a robot in a maze environment. Users can either start to construct networks from scratch or elaborate on networks created by other users. In particular, Brain...

  8. The minimum spanning tree : An unbiased method for brain network analysis

    NARCIS (Netherlands)

    Tewarie, P.; van Dellen, E.; Hillebrand, A.; Stam, C. J.

    2015-01-01

    The brain is increasingly studied with graph theoretical approaches, which can be used to characterize network topology. However, studies on brain networks have reported contradictory findings, and do not easily converge to a clear concept of the structural and functional network organization of the

  9. Emotion Regulation and Complex Brain Networks: Association Between Expressive Suppression and Efficiency in the Fronto-Parietal Network and Default-Mode Network

    Directory of Open Access Journals (Sweden)

    Junhao Pan

    2018-03-01

    Full Text Available Emotion regulation (ER refers to the “implementation of a conscious or non-conscious goal to start, stop or otherwise modulate the trajectory of an emotion” (Etkin et al., 2015. Whereas multiple brain areas have been found to be involved in ER, relatively little is known about whether and how ER is associated with the global functioning of brain networks. Recent advances in brain connectivity research using graph-theory based analysis have shown that the brain can be organized into complex networks composed of functionally or structurally connected brain areas. Global efficiency is one graphic metric indicating the efficiency of information exchange among brain areas and is utilized to measure global functioning of brain networks. The present study examined the relationship between trait measures of ER (expressive suppression (ES and cognitive reappraisal (CR and global efficiency in resting-state functional brain networks (the whole brain network and ten predefined networks using structural equation modeling (SEM. The results showed that ES was reliably associated with efficiency in the fronto-parietal network and default-mode network. The finding advances the understanding of neural substrates of ER, revealing the relationship between ES and efficient organization of brain networks.

  10. Natural language acquisition in large scale neural semantic networks

    Science.gov (United States)

    Ealey, Douglas

    This thesis puts forward the view that a purely signal- based approach to natural language processing is both plausible and desirable. By questioning the veracity of symbolic representations of meaning, it argues for a unified, non-symbolic model of knowledge representation that is both biologically plausible and, potentially, highly efficient. Processes to generate a grounded, neural form of this model-dubbed the semantic filter-are discussed. The combined effects of local neural organisation, coincident with perceptual maturation, are used to hypothesise its nature. This theoretical model is then validated in light of a number of fundamental neurological constraints and milestones. The mechanisms of semantic and episodic development that the model predicts are then used to explain linguistic properties, such as propositions and verbs, syntax and scripting. To mimic the growth of locally densely connected structures upon an unbounded neural substrate, a system is developed that can grow arbitrarily large, data- dependant structures composed of individual self- organising neural networks. The maturational nature of the data used results in a structure in which the perception of concepts is refined by the networks, but demarcated by subsequent structure. As a consequence, the overall structure shows significant memory and computational benefits, as predicted by the cognitive and neural models. Furthermore, the localised nature of the neural architecture also avoids the increasing error sensitivity and redundancy of traditional systems as the training domain grows. The semantic and episodic filters have been demonstrated to perform as well, or better, than more specialist networks, whilst using significantly larger vocabularies, more complex sentence forms and more natural corpora.

  11. A Novel Human Body Area Network for Brain Diseases Analysis.

    Science.gov (United States)

    Lin, Kai; Xu, Tianlang

    2016-10-01

    Development of wireless sensor and mobile communication technology provide an unprecedented opportunity for realizing smart and interactive healthcare systems. Designing such systems aims to remotely monitor the health and diagnose the diseases for users. In this paper, we design a novel human body area network for brain diseases analysis, which is named BABDA. Considering the brain is one of the most complex organs in the human body, the BABDA system provides four function modules to ensure the high quality of the analysis result, which includes initial data collection, data correction, data transmission and comprehensive data analysis. The performance evaluation conducted in a realistic environment with several criteria shows the availability and practicability of the BABDA system.

  12. Metabolic Brain Network Analysis of Hypothyroidism Symptom Based on [18F]FDG-PET of Rats.

    Science.gov (United States)

    Wan, Hongkai; Tan, Ziyu; Zheng, Qiang; Yu, Jing

    2018-03-12

    Recent researches have demonstrated the value of using 2-deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) positron emission tomography (PET) imaging to reveal the hypothyroidism-related damages in local brain regions. However, the influence of hypothyroidism on the entire brain network is barely studied. This study focuses on the application of graph theory on analyzing functional brain networks of the hypothyroidism symptom. For both the hypothyroidism and the control groups of Wistar rats, the functional brain networks were constructed by thresholding the glucose metabolism correlation matrices of 58 brain regions. The network topological properties (including the small-world properties and the nodal centralities) were calculated and compared between the two groups. We found that the rat brains, like human brains, have typical properties of the small-world network in both the hypothyroidism and the control groups. However, the hypothyroidism group demonstrated lower global efficiency and decreased local cliquishness of the brain network, indicating hypothyroidism-related impairment to the brain network. The hypothyroidism group also has decreased nodal centrality in the left posterior hippocampus, the right hypothalamus, pituitary, pons, and medulla. This observation accorded with the hypothyroidism-related functional disorder of hypothalamus-pituitary-thyroid (HPT) feedback regulation mechanism. Our research quantitatively confirms that hypothyroidism hampers brain cognitive function by causing impairment to the brain network of glucose metabolism. This study reveals the feasibility and validity of applying graph theory method to preclinical [ 18 F]FDG-PET images and facilitates future study on human subjects.

  13. Teaching Pronunciation to Adult English Language Learners. CAELA Network Brief

    Science.gov (United States)

    Schaetzel, Kirsten; Low, Ee Ling

    2009-01-01

    Adult English language learners in the United States approach the learning of English pronunciation from a wide variety of native language backgrounds. They may speak languages with sound systems that vary a great deal from that of English. The pronunciation goals and needs of adult English language learners are diverse. These goals and needs…

  14. Age-Related Differences in the Brain Areas outside the Classical Language Areas among Adults Using Category Decision Task

    Science.gov (United States)

    Cho, Yong Won; Song, Hui-Jin; Lee, Jae Jun; Lee, Joo Hwa; Lee, Hui Joong; Yi, Sang Doe; Chang, Hyuk Won; Berl, Madison M.; Gaillard, William D.; Chang, Yongmin

    2012-01-01

    Older adults perform much like younger adults on language. This similar level of performance, however, may come about through different underlying brain processes. In the present study, we evaluated age-related differences in the brain areas outside the typical language areas among adults using a category decision task. Our results showed that…

  15. Toward a Coevolution of Language Theories: Linking Composition with Brain and Language Studies.

    Science.gov (United States)

    Adkison, Stephen

    Focusing specifically on the theories offered by language development theorist L. S. Vygotsky and evolutionary theorist Terrence Deacon, this paper examines the ways in which theories of language in composition studies coincide and differ with the theories currently being researched in neurobiology and physical anthropology. This examination…

  16. The mirror brain, concepts, and language: the price of anthropogenesis.

    Science.gov (United States)

    Chernigovskaya, T V

    2007-03-01

    This article presents a review of cognitive evolution and the question of the origin of language and consciousness. Questions of the genetic history of Homo sapiens are considered, along with basic concepts and their relationship to sensory experience. The questions of the location of higher functions and the organization of metarepresentations in health and pathology are discussed.

  17. Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

    OpenAIRE

    Xerxes D. Arsiwalla; Riccardo eZucca; Alberto eBetella; Enrique eMartinez; David eDalmazzo; Pedro eOmedas; Gustavo eDeco; Gustavo eDeco; Paul F.M.J. Verschure; Paul F.M.J. Verschure

    2015-01-01

    BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

  18. Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

    OpenAIRE

    Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martínez, Enrique, 1961-; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

    2015-01-01

    BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

  19. Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images.

    Science.gov (United States)

    Pereira, Sergio; Pinto, Adriano; Alves, Victor; Silva, Carlos A

    2016-05-01

    Among brain tumors, gliomas are the most common and aggressive, leading to a very short life expectancy in their highest grade. Thus, treatment planning is a key stage to improve the quality of life of oncological patients. Magnetic resonance imaging (MRI) is a widely used imaging technique to assess these tumors, but the large amount of data produced by MRI prevents manual segmentation in a reasonable time, limiting the use of precise quantitative measurements in the clinical practice. So, automatic and reliable segmentation methods are required; however, the large spatial and structural variability among brain tumors make automatic segmentation a challenging problem. In this paper, we propose an automatic segmentation method based on Convolutional Neural Networks (CNN), exploring small 3 ×3 kernels. The use of small kernels allows designing a deeper architecture, besides having a positive effect against overfitting, given the fewer number of weights in the network. We also investigated the use of intensity normalization as a pre-processing step, which though not common in CNN-based segmentation methods, proved together with data augmentation to be very effective for brain tumor segmentation in MRI images. Our proposal was validated in the Brain Tumor Segmentation Challenge 2013 database (BRATS 2013), obtaining simultaneously the first position for the complete, core, and enhancing regions in Dice Similarity Coefficient metric (0.88, 0.83, 0.77) for the Challenge data set. Also, it obtained the overall first position by the online evaluation platform. We also participated in the on-site BRATS 2015 Challenge using the same model, obtaining the second place, with Dice Similarity Coefficient metric of 0.78, 0.65, and 0.75 for the complete, core, and enhancing regions, respectively.

  20. Analysis of structure-function network decoupling in the brain systems of spastic diplegic cerebral palsy.

    Science.gov (United States)

    Lee, Dongha; Pae, Chongwon; Lee, Jong Doo; Park, Eun Sook; Cho, Sung-Rae; Um, Min-Hee; Lee, Seung-Koo; Oh, Maeng-Keun; Park, Hae-Jeong

    2017-10-01

    Manifestation of the functionalities from the structural brain network is becoming increasingly important to understand a brain disease. With the aim of investigating the differential structure-function couplings according to network systems, we investigated the structural and functional brain networks of patients with spastic diplegic cerebral palsy with periventricular leukomalacia compared to healthy controls. The structural and functional networks of the whole brain and motor system, constructed using deterministic and probabilistic tractography of diffusion tensor magnetic resonance images and Pearson and partial correlation analyses of resting-state functional magnetic resonance images, showed differential embedding of functional networks in the structural networks in patients. In the whole-brain network of patients, significantly reduced global network efficiency compared to healthy controls were found in the structural networks but not in the functional networks, resulting in reduced structural-functional coupling. On the contrary, the motor network of patients had a significantly lower functional network efficiency over the intact structural network and a lower structure-function coupling than the control group. This reduced coupling but reverse directionality in the whole-brain and motor networks of patients was prominent particularly between the probabilistic structural and partial correlation-based functional networks. Intact (or less deficient) functional network over impaired structural networks of the whole brain and highly impaired functional network topology over the intact structural motor network might subserve relatively preserved cognitions and impaired motor functions in cerebral palsy. This study suggests that the structure-function relationship, evaluated specifically using sparse functional connectivity, may reveal important clues to functional reorganization in cerebral palsy. Hum Brain Mapp 38:5292-5306, 2017. © 2017 Wiley Periodicals

  1. Drawing Inspiration from Human Brain Networks: Construction of Interconnected Virtual Networks.

    Science.gov (United States)

    Murakami, Masaya; Kominami, Daichi; Leibnitz, Kenji; Murata, Masayuki

    2018-04-08

    Virtualization of wireless sensor networks (WSN) is widely considered as a foundational block of edge/fog computing, which is a key technology that can help realize next-generation Internet of things (IoT) networks. In such scenarios, multiple IoT devices and service modules will be virtually deployed and interconnected over the Internet. Moreover, application services are expected to be more sophisticated and complex, thereby increasing the number of modifications required for the construction of network topologies. Therefore, it is imperative to establish a method for constructing a virtualized WSN (VWSN) topology that achieves low latency on information transmission and high resilience against network failures, while keeping the topological construction cost low. In this study, we draw inspiration from inter-modular connectivity in human brain networks, which achieves high performance when dealing with large-scale networks composed of a large number of modules (i.e., regions) and nodes (i.e., neurons). We propose a method for assigning inter-modular links based on a connectivity model observed in the cerebral cortex of the brain, known as the exponential distance rule (EDR) model. We then choose endpoint nodes of these links by controlling inter-modular assortativity, which characterizes the topological connectivity of brain networks. We test our proposed methods using simulation experiments. The results show that the proposed method based on the EDR model can construct a VWSN topology with an optimal combination of communication efficiency, robustness, and construction cost. Regarding the selection of endpoint nodes for the inter-modular links, the results also show that high assortativity enhances the robustness and communication efficiency because of the existence of inter-modular links of two high-degree nodes.

  2. Language Impairments in ASD Resulting from a Failed Domestication of the Human Brain

    Science.gov (United States)

    Benítez-Burraco, Antonio; Lattanzi, Wanda; Murphy, Elliot

    2016-01-01

    Autism spectrum disorders (ASD) are pervasive neurodevelopmental disorders entailing social and cognitive deficits, including marked problems with language. Numerous genes have been associated with ASD, but it is unclear how language deficits arise from gene mutation or dysregulation. It is also unclear why ASD shows such high prevalence within human populations. Interestingly, the emergence of a modern faculty of language has been hypothesized to be linked to changes in the human brain/skull, but also to the process of self-domestication of the human species. It is our intention to show that people with ASD exhibit less marked domesticated traits at the morphological, physiological, and behavioral levels. We also discuss many ASD candidates represented among the genes known to be involved in the “domestication syndrome” (the constellation of traits exhibited by domesticated mammals, which seemingly results from the hypofunction of the neural crest) and among the set of genes involved in language function closely connected to them. Moreover, many of these genes show altered expression profiles in the brain of autists. In addition, some candidates for domestication and language-readiness show the same expression profile in people with ASD and chimps in different brain areas involved in language processing. Similarities regarding the brain oscillatory behavior of these areas can be expected too. We conclude that ASD may represent an abnormal ontogenetic itinerary for the human faculty of language resulting in part from changes in genes important for the “domestication syndrome” and, ultimately, from the normal functioning of the neural crest. PMID:27621700

  3. Stable functional networks exhibit consistent timing in the human brain.

    Science.gov (United States)

    Chapeton, Julio I; Inati, Sara K; Zaghloul, Kareem A

    2017-03-01

    Despite many advances in the study of large-scale human functional networks, the question of timing, stability, and direction of communication between cortical regions has not been fully addressed. At the cellular level, neuronal communication occurs through axons and dendrites, and the time required for such communication is well defined and preserved. At larger spatial scales, however, the relationship between timing, direction, and communication between brain regions is less clear. Here, we use a measure of effective connectivity to identify connections between brain regions that exhibit communication with consistent timing. We hypothesized that if two brain regions are communicating, then knowledge of the activity in one region should allow an external observer to better predict activity in the other region, and that such communication involves a consistent time delay. We examine this question using intracranial electroencephalography captured from nine human participants with medically refractory epilepsy. We use a coupling measure based on time-lagged mutual information to identify effective connections between brain regions that exhibit a statistically significant increase in average mutual information at a consistent time delay. These identified connections result in sparse, directed functional networks that are stable over minutes, hours, and days. Notably, the time delays associated with these connections are also highly preserved over multiple time scales. We characterize the anatomic locations of these connections, and find that the propagation of activity exhibits a preferred posterior to anterior temporal lobe direction, consistent across participants. Moreover, networks constructed from connections that reliably exhibit consistent timing between anatomic regions demonstrate features of a small-world architecture, with many reliable connections between anatomically neighbouring regions and few long range connections. Together, our results demonstrate

  4. Bilingualism alters brain functional connectivity between "control" regions and "language" regions: Evidence from bimodal bilinguals.

    Science.gov (United States)

    Li, Le; Abutalebi, Jubin; Zou, Lijuan; Yan, Xin; Liu, Lanfang; Feng, Xiaoxia; Wang, Ruiming; Guo, Taomei; Ding, Guosheng

    2015-05-01

    Previous neuroimaging studies have revealed that bilingualism induces both structural and functional neuroplasticity in the dorsal anterior cingulate cortex (dACC) and the left caudate nucleus (LCN), both of which are associated with cognitive control. Since these "control" regions should work together with other language regions during language processing, we hypothesized that bilingualism may also alter the functional interaction between the dACC/LCN and language regions. Here we tested this hypothesis by exploring the functional connectivity (FC) in bimodal bilinguals and monolinguals using functional MRI when they either performed a picture naming task with spoken language or were in resting state. We found that for bimodal bilinguals who use spoken and sign languages, the FC of the dACC with regions involved in spoken language (e.g. the left superior temporal gyrus) was stronger in performing the task, but weaker in the resting state as compared to monolinguals. For the LCN, its intrinsic FC with sign language regions including the left inferior temporo-occipital part and right inferior and superior parietal lobules was increased in the bilinguals. These results demonstrate that bilingual experience may alter the brain functional interaction between "control" regions and "language" regions. For different control regions, the FC alters in different ways. The findings also deepen our understanding of the functional roles of the dACC and LCN in language processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

  5. Brain imaging of language plasticity in adopted adults: can a second language replace the first?

    Science.gov (United States)

    Pallier, C; Dehaene, S; Poline, J-B; LeBihan, D; Argenti, A-M; Dupoux, E; Mehler, J

    2003-02-01

    Do the neural circuits that subserve language acquisition lose plasticity as they become tuned to the maternal language? We tested adult subjects born in Korea and adopted by French families in childhood; they have become fluent in their second language and report no conscious recollection of their native language. In behavioral tests assessing their memory for Korean, we found that they do not perform better than a control group of native French subjects who have never been exposed to Korean. We also used event-related functional magnetic resonance imaging to monitor cortical activations while the Korean adoptees and native French listened to sentences spoken in Korean, French and other, unknown, foreign languages. The adopted subjects did not show any specific activations to Korean stimuli relative to unknown languages. The areas activated more by French stimuli than by foreign stimuli were similar in the Korean adoptees and in the French native subjects, but with relatively larger extents of activation in the latter group. We discuss these data in light of the critical period hypothesis for language acquisition.

  6. Quetiapine modulates functional connectivity in brain aggression networks.

    Science.gov (United States)

    Klasen, Martin; Zvyagintsev, Mikhail; Schwenzer, Michael; Mathiak, Krystyna A; Sarkheil, Pegah; Weber, René; Mathiak, Klaus

    2013-07-15

    Aggressive behavior is associated with dysfunctions in an affective regulation network encompassing amygdala and prefrontal areas such as orbitofrontal (OFC), anterior cingulate (ACC), and dorsolateral prefrontal cortex (DLPFC). In particular, prefrontal regions have been postulated to control amygdala activity by inhibitory projections, and this process may be disrupted in aggressive individuals. The atypical antipsychotic quetiapine successfully attenuates aggressive behavior in various disorders; the underlying neural processes, however, are unknown. A strengthened functional coupling in the prefrontal-amygdala system may account for these anti-aggressive effects. An inhibition of this network has been reported for virtual aggression in violent video games as well. However, there have been so far no in-vivo observations of pharmacological influences on corticolimbic projections during human aggressive behavior. In a double-blind, placebo-controlled study, quetiapine and placebo were administered for three successive days prior to an fMRI experiment. In this experiment, functional brain connectivity was assessed during virtual aggressive behavior in a violent video game and an aggression-free control task in a non-violent modification. Quetiapine increased the functional connectivity of ACC and DLPFC with the amygdala during virtual aggression, whereas OFC-amygdala coupling was attenuated. These effects were observed neither for placebo nor for the non-violent control. These results demonstrate for the first time a pharmacological modification of aggression-related human brain networks in a naturalistic setting. The violence-specific modulation of prefrontal-amygdala networks appears to control aggressive behavior and provides a neurobiological model for the anti-aggressive effects of quetiapine. Copyright © 2013 Elsevier Inc. All rights reserved.

  7. Potential language and attentional networks revealed through factor analysis of rCBF data measured with SPECT

    DEFF Research Database (Denmark)

    McLaughlin, T; Steinberg, B; Christensen, B

    1992-01-01

    We used changes in regional cerebral blood flow (rCBF) to disclose regions involved in central auditory and language processing in the normal brain. rCBF was quantified with a fast-rotating, single-photon emission computerized tomograph (SPECT) and inhalation of 133Xe. rCBF data were obtained sim...... brain networks involved in (I) auditory/linguistic, (II) attentional, and (III) visual imaging activity.......We used changes in regional cerebral blood flow (rCBF) to disclose regions involved in central auditory and language processing in the normal brain. rCBF was quantified with a fast-rotating, single-photon emission computerized tomograph (SPECT) and inhalation of 133Xe. rCBF data were obtained...... simultaneously from parallel, transverse slices of the brain. The lower slice was positioned to include both Broca's and Wernicke's areas. The upper slice included regions generally regarded by neurobehaviorists as less related to primary auditory or linguistic functions. We presented three types of auditory...

  8. Plasticity in the Developing Brain: Intellectual, Language and Academic Functions in Children with Ischaemic Perinatal Stroke

    Science.gov (United States)

    Ballantyne, Angela O.; Spilkin, Amy M.; Hesselink, John; Trauner, Doris A.

    2008-01-01

    The developing brain has the capacity for a great deal of plasticity. A number of investigators have demonstrated that intellectual and language skills may be in the normal range in children following unilateral perinatal stroke. Questions have been raised, however, about whether these skills can be maintained at the same level as the brain…

  9. Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics

    Science.gov (United States)

    Bonaiuto, James J.; Bornkessel-Schlesewsky, Ina; Kemmerer, David; MacWhinney, Brian; Nielsen, Finn Årup; Oztop, Erhan

    2014-01-01

    We assess the challenges of studying action and language mechanisms in the brain, both singly and in relation to each other to provide a novel perspective on neuroinformatics, integrating the development of databases for encoding – separately or together – neurocomputational models and empirical data that serve systems and cognitive neuroscience. PMID:24234916

  10. Academic and Language Outcomes in Children after Traumatic Brain Injury: A Meta-Analysis

    Science.gov (United States)

    Vu, Jennifer A.; Babikian, Talin; Asarnow, Robert F .

    2011-01-01

    Expanding on Babikian and Asarnow's (2009) meta-analytic study examining neurocognitive domains, this current meta-analysis examined academic and language outcomes at different time points post-traumatic brain injury (TBI) in children and adolescents. Although children with mild TBI exhibited no significant deficits, studies indicate that children…

  11. Action and Language Mechanisms in the Brain: Data, Models and Neuroinformatics

    DEFF Research Database (Denmark)

    Arbib, Michael A.; Bonaiuto, James J.; Bornkessel-Schlesewsky, Ina

    2014-01-01

    We assess the challenges of studying action and language mechanisms in the brain, both singly and in relation to each other to provide a novel perspective on neuroinformatics, integrating the development of databases for encoding - separately or together - neurocomputational models and empirical ...

  12. Atypical Brain Responses to Sounds in Children with Specific Language and Reading Impairments

    Science.gov (United States)

    McArthur, Genevieve; Atkinson, Carmen; Ellis, Danielle

    2009-01-01

    This study tested if children with specific language impairment (SLI) or children with specific reading disability (SRD) have abnormal brain responses to sounds. We tested 6- to 12-year-old children with SLI (N = 19), children with SRD (N = 55), and age-matched controls (N = 36) for their passive auditory event-related potentials (ERPs) to tones,…

  13. Comparison of brain MRI findings with language and motor function in the dystroglycanopathies.

    Science.gov (United States)

    Brun, Brianna N; Mockler, Shelley R H; Laubscher, Katie M; Stephan, Carrie M; Wallace, Anne M; Collison, Julia A; Zimmerman, M Bridget; Dobyns, William B; Mathews, Katherine D

    2017-02-14

    To describe the spectrum of brain MRI findings in a cohort of individuals with dystroglycanopathies (DGs) and relate MRI results to function. All available brain MRIs done for clinical indications on individuals enrolled in a DG natural history study (NCT00313677) were reviewed. Reports were reviewed when MRI was not available. MRIs were categorized as follows: (1) cortical, brainstem, and cerebellar malformations; (2) cortical and cerebellar malformations; or (3) normal. Language development was assigned to 1 of 3 categories by a speech pathologist. Maximal motor function and presence of epilepsy were determined by history or examination. Twenty-five MRIs and 9 reports were reviewed. The most common MRI abnormalities were cobblestone cortex or dysgyria with an anterior-posterior gradient and cerebellar hypoplasia. Seven individuals had MRIs in group 1, 8 in group 2, and 19 in group 3. Language was impaired in 100% of those in MRI groups 1 and 2, and degree of language impairment correlated with severity of imaging. Eighty-five percent of the whole group achieved independent walking, but only 33% did in group 1. Epilepsy was present in 8% of the cohort and rose to 37% of those with an abnormal MRI. Developmental abnormalities of the brain such as cobblestone lissencephaly, cerebellar cysts, pontine hypoplasia, and brainstem bowing are hallmarks of DG and should prompt consideration of these diagnoses. Brain imaging in individuals with DG helps to predict outcomes, especially language development, aiding clinicians in prognostic counseling. © 2017 American Academy of Neurology.

  14. Two Languages, One Developing Brain: Event-Related Potentials to Words in Bilingual Toddlers

    Science.gov (United States)

    Conboy, Barbara T.; Mills, Debra L.

    2006-01-01

    Infant bilingualism offers a unique opportunity to study the relative effects of language experience and maturation on brain development, with each child serving as his or her own control. Event-related potentials (ERPs) to words were examined in 19- to 22-month-old English-Spanish bilingual toddlers. The children's dominant vs. nondominant…

  15. A Mapping Between Structural and Functional Brain Networks.

    Science.gov (United States)

    Meier, Jil; Tewarie, Prejaas; Hillebrand, Arjan; Douw, Linda; van Dijk, Bob W; Stufflebeam, Steven M; Van Mieghem, Piet

    2016-05-01

    The relationship between structural and functional brain networks is still highly debated. Most previous studies have used a single functional imaging modality to analyze this relationship. In this work, we use multimodal data, from functional MRI, magnetoencephalography, and diffusion tensor imaging, and assume that there exists a mapping between the connectivity matrices of the resting-state functional and structural networks. We investigate this mapping employing group averaged as well as individual data. We indeed find a significantly high goodness of fit level for this structure-function mapping. Our analysis suggests that a functional connection is shaped by all walks up to the diameter in the structural network in both modality cases. When analyzing the inverse mapping, from function to structure, longer walks in the functional network also seem to possess minor influence on the structural connection strengths. Even though similar overall properties for the structure-function mapping are found for different functional modalities, our results indicate that the structure-function relationship is modality dependent.

  16. Brain networks and their origins. Comment on “Understanding brain networks and brain organization” by Luiz Pessoa

    Science.gov (United States)

    Cisek, Paul

    2014-09-01

    Nearly every textbook on psychology or neuroscience contains theories of function described with box and arrow diagrams. Sometimes, the boxes stand for purely theoretical constructs, such as attention or working memory, and sometimes they also correspond to specific brain regions or systems, such as parietal or prefrontal cortex, and the arrows between them to known anatomical pathways. It is common for scientists (present company included) to summarize their theories in this way and to think of the brain as a set of interacting modules with clearly distinguishable functions.

  17. Brain-based translation: fMRI decoding of spoken words in bilinguals reveals language-independent semantic representations in anterior temporal lobe.

    Science.gov (United States)

    Correia, João; Formisano, Elia; Valente, Giancarlo; Hausfeld, Lars; Jansma, Bernadette; Bonte, Milene

    2014-01-01

    Bilinguals derive the same semantic concepts from equivalent, but acoustically different, words in their first and second languages. The neural mechanisms underlying the representation of language-independent concepts in the brain remain unclear. Here, we measured fMRI in human bilingual listeners and reveal that response patterns to individual spoken nouns in one language (e.g., "horse" in English) accurately predict the response patterns to equivalent nouns in the other language (e.g., "paard" in Dutch). Stimuli were four monosyllabic words in both languages, all from the category of "animal" nouns. For each word, pronunciations from three different speakers were included, allowing the investigation of speaker-independent representations of individual words. We used multivariate classifiers and a searchlight method to map the informative fMRI response patterns that enable decoding spoken words within languages (within-language discrimination) and across languages (across-language generalization). Response patterns discriminative of spoken words within language were distributed in multiple cortical regions, reflecting the complexity of the neural networks recruited during speech and language processing. Response patterns discriminative of spoken words across language were limited to localized clusters in the left anterior temporal lobe, the left angular gyrus and the posterior bank of the left postcentral gyrus, the right posterior superior temporal sulcus/superior temporal gyrus, the right medial anterior temporal lobe, the right anterior insula, and bilateral occipital cortex. These results corroborate the existence of "hub" regions organizing semantic-conceptual knowledge in abstract form at the fine-grained level of within semantic category discriminations.

  18. A Time and Place for Language Comprehension: Mapping the N400 and the P600 to a Minimal Cortical Network

    Directory of Open Access Journals (Sweden)

    Harm eBrouwer

    2013-11-01

    Full Text Available We propose a new functional-anatomical mapping of the N400 and the P600 toa minimal cortical network for language comprehension. Our work is anexample of a recent research strategy in cognitive neuroscience, whereresearchers attempt to align data regarding the nature and time-course ofcognitive processing (from ERPs with data on the cortical organizationunderlying it (from fMRI. The success of this `alignment' approachcritically depends on the functional interpretation of relevant ERPcomponents. Models of language processing that have been proposed thus fardo not agree on these interpretations, and present a variety of complicatedfunctional architectures. We put forward a very basic functional-anatomicalmapping based on the recently developed Retrieval-Integration account oflanguage comprehension (Brouwer, Fitz, & Hoeks, 2012. In this mapping, the leftposterior part of the Middle Temporal Gyrus (BA 21 serves as anepicenter (or hub in a neurocognitive network for theretrieval of word meaning, the ease of which is reflected in N400 amplitude.The left Inferior Frontal Gyrus (BA 44/45/47, in turn, serves a networkepicenter for the integration of this retrieved meaning with the word'spreceding context, into a mental representation of what is beingcommunicated; these semantic and pragmatic integrative processes arereflected in P600 amplitude. We propose that our mapping describes the coreof the language comprehension network, a view that is parsimonious, hasbroad empirical coverage, and can serve as the starting point for a morefocused investigation into the coupling of brain anatomy andelectrophysiology.

  19. Using Neural Networks to Generate Inferential Roles for Natural Language

    Directory of Open Access Journals (Sweden)

    Peter Blouw

    2018-01-01

    Full Text Available Neural networks have long been used to study linguistic phenomena spanning the domains of phonology, morphology, syntax, and semantics. Of these domains, semantics is somewhat unique in that there is little clarity concerning what a model needs to be able to do in order to provide an account of how the meanings of complex linguistic expressions, such as sentences, are understood. We argue that one thing such models need to be able to do is generate predictions about which further sentences are likely to follow from a given sentence; these define the sentence's “inferential role.” We then show that it is possible to train a tree-structured neural network model to generate very simple examples of such inferential roles using the recently released Stanford Natural Language Inference (SNLI dataset. On an empirical front, we evaluate the performance of this model by reporting entailment prediction accuracies on a set of test sentences not present in the training data. We also report the results of a simple study that compares human plausibility ratings for both human-generated and model-generated entailments for a random selection of sentences in this test set. On a more theoretical front, we argue in favor of a revision to some common assumptions about semantics: understanding a linguistic expression is not only a matter of mapping it onto a representation that somehow constitutes its meaning; rather, understanding a linguistic expression is mainly a matter of being able to draw certain inferences. Inference should accordingly be at the core of any model of semantic cognition.

  20. The effects of music on brain functional networks: a network analysis.

    Science.gov (United States)

    Wu, J; Zhang, J; Ding, X; Li, R; Zhou, C

    2013-10-10

    The human brain can dynamically adapt to the changing surroundings. To explore this issue, we adopted graph theoretical tools to examine changes in electroencephalography (EEG) functional networks while listening to music. Three different excerpts of Chinese Guqin music were played to 16 non-musician subjects. For the main frequency intervals, synchronizations between all pair-wise combinations of EEG electrodes were evaluated with phase lag index (PLI). Then, weighted connectivity networks were created and their organizations were characterized in terms of an average clustering coefficient and characteristic path length. We found an enhanced synchronization level in the alpha2 band during music listening. Music perception showed a decrease of both normalized clustering coefficient and path length in the alpha2 band. Moreover, differences in network measures were not observed between musical excerpts. These experimental results demonstrate an increase of functional connectivity as well as a more random network structure in the alpha2 band during music perception. The present study offers support for the effects of music on human brain functional networks with a trend toward a more efficient but less economical architecture. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

  1. Investigating a Novel Measure of Brain Networking Following Sports Concussion.

    Science.gov (United States)

    Broglio, S P; Rettmann, A; Greer, J; Brimacombe, S; Moore, B; Narisetty, N; He, X; Eckner, J

    2016-08-01

    Clinicians managing sports-related concussions are left to their clinical judgment in making diagnoses and return-to-play decisions. This study was designed to evaluate the utility of a novel measure of functional brain networking for concussion management. 24 athletes with acutely diagnosed concussion and 21 control participants were evaluated in a research laboratory. At each of the 4 post-injury time points, participants completed the Axon assessment of neurocognitive function, a self-report symptom inventory, and the auditory oddball and go/no-go tasks while electroencephalogram (EEG) readings were recorded. Brain Network Activation (BNA) scores were calculated from EEG data related to the auditory oddball and go/no-go tasks. BNA scores were unable to differentiate between the concussed and control groups or by self-report symptom severity. These findings conflict with previous work implementing electrophysiological assessments in concussed athletes, suggesting that BNA requires additional investigation and refinement before clinical implementation. © Georg Thieme Verlag KG Stuttgart · New York.

  2. Classification of CT brain images based on deep learning networks.

    Science.gov (United States)

    Gao, Xiaohong W; Hui, Rui; Tian, Zengmin

    2017-01-01

    While computerised tomography (CT) may have been the first imaging tool to study human brain, it has not yet been implemented into clinical decision making process for diagnosis of Alzheimer's disease (AD). On the other hand, with the nature of being prevalent, inexpensive and non-invasive, CT does present diagnostic features of AD to a great extent. This study explores the significance and impact on the application of the burgeoning deep learning techniques to the task of classification of CT brain images, in particular utilising convolutional neural network (CNN), aiming at providing supplementary information for the early diagnosis of Alzheimer's disease. Towards this end, three categories of CT images (N = 285) are clustered into three groups, which are AD, lesion (e.g. tumour) and normal ageing. In addition, considering the characteristics of this collection with larger thickness along the direction of depth (z) (~3-5 mm), an advanced CNN architecture is established integrating both 2D and 3D CNN networks. The fusion of the two CNN networks is subsequently coordinated based on the average of Softmax scores obtained from both networks consolidating 2D images along spatial axial directions and 3D segmented blocks respectively. As a result, the classification accuracy rates rendered by this elaborated CNN architecture are 85.2%, 80% and 95.3% for classes of AD, lesion and normal respectively with an average of 87.6%. Additionally, this improved CNN network appears to outperform the others when in comparison with 2D version only of CNN network as well as a number of state of the art hand-crafted approaches. As a result, these approaches deliver accuracy rates in percentage of 86.3, 85.6 ± 1.10, 86.3 ± 1.04, 85.2 ± 1.60, 83.1 ± 0.35 for 2D CNN, 2D SIFT, 2D KAZE, 3D SIFT and 3D KAZE respectively. The two major contributions of the paper constitute a new 3-D approach while applying deep learning technique to extract signature information

  3. Dismissing attachment characteristics dynamically modulate brain networks subserving social aversion.

    Directory of Open Access Journals (Sweden)

    Anna Linda eKrause

    2016-03-01

    Full Text Available Attachment patterns influence actions, thoughts and feeling through a person’s ‘Inner Working Model’. Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest fMRI-experiment, presenting auditory narratives prototypical of dismissing attachment representations to investigate their effect on 23 healthy males. We then examined effects of participants’ attachment style and childhood trauma on brain state changes using seed-based functional connectivity (FC analyses, and finally tested whether subjective differences in responsivity to narratives could be predicted by baseline network states. In comparison to a baseline state, we observed increased FC in a previously described ‘social aversion network’ including dorsal anterior cingulated cortex (dACC and left anterior middle temporal gyrus (aMTG specifically after exposure to insecure-dismissing attachment narratives. Increased dACC-seeded FC within the social aversion network was positively related to the participants’ avoidant attachment style and presence of a history of childhood trauma. Anxious attachment style on the other hand was positively correlated with FC between the dACC and a region outside of the ‘social aversion network’, namely the dorsolateral prefrontal cortex, which suggests decreased network segregation as a function of anxious attachment. Finally, the extent of subjective experience of friendliness towards the dismissing narrative was predicted by low baseline FC-values between hippocampus and inferior parietal lobule. Taken together, our study demonstrates an activation of networks related to social aversion in terms of increased connectivity after listening to insecure-dismissing attachment narratives. A causal interrelation of brain state changes and subsequent changes in social reactivity was further supported by our observation of direct

  4. Language control in bilingual adults with and without history of mild traumatic brain injury.

    Science.gov (United States)

    Ratiu, Ileana; Azuma, Tamiko

    2017-03-01

    Adults with a history of traumatic brain injury often show deficits in executive functioning (EF), including the ability to inhibit, switch, and attend to tasks. These abilities are critical for language processing in bilinguals. This study examined the effect of mild traumatic brain injury (mTBI) on EF and language processing in bilinguals using behavioral and eye-tracking measures. Twenty-two bilinguals with a history of mTBI and twenty healthy control bilinguals were administered executive function and language processing tasks. Bilinguals with a history of mTBI showed deficits in specific EFs and had higher rates of language processing errors than healthy control bilinguals. Additionally, individuals with a history of mTBI have different patterns of eye movements during reading than healthy control bilinguals. These data suggest that language processing deficits are related to underlying EF abilities. The findings provide important information regarding specific EF and language control deficits in bilinguals with a history mTBI. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Brain white matter structure and COMT gene are linked to second-language learning in adults.

    Science.gov (United States)

    Mamiya, Ping C; Richards, Todd L; Coe, Bradley P; Eichler, Evan E; Kuhl, Patricia K

    2016-06-28

    Adult human brains retain the capacity to undergo tissue reorganization during second-language learning. Brain-imaging studies show a relationship between neuroanatomical properties and learning for adults exposed to a second language. However, the role of genetic factors in this relationship has not been investigated. The goal of the current study was twofold: (i) to characterize the relationship between brain white matter fiber-tract properties and second-language immersion using diffusion tensor imaging, and (ii) to determine whether polymorphisms in the catechol-O-methyltransferase (COMT) gene affect the relationship. We recruited incoming Chinese students enrolled in the University of Washington and scanned their brains one time. We measured the diffusion properties of the white matter fiber tracts and correlated them with the number of days each student had been in the immersion program at the time of the brain scan. We found that higher numbers of days in the English immersion program correlated with higher fractional anisotropy and lower radial diffusivity in the right superior longitudinal fasciculus. We show that fractional anisotropy declined once the subjects finished the immersion program. The relationship between brain white matter fiber-tract properties and immersion varied in subjects with different COMT genotypes. Subjects with the Methionine (Met)/Valine (Val) and Val/Val genotypes showed higher fractional anisotropy and lower radial diffusivity during immersion, which reversed immediately after immersion ended, whereas those with the Met/Met genotype did not show these relationships. Statistical modeling revealed that subjects' grades in the language immersion program were best predicted by fractional anisotropy and COMT genotype.

  6. Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders

    Directory of Open Access Journals (Sweden)

    Qingying Meng

    2016-05-01

    Full Text Available Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient–host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control and hippocampus (cognitive processing from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine.

  7. Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders.

    Science.gov (United States)

    Meng, Qingying; Ying, Zhe; Noble, Emily; Zhao, Yuqi; Agrawal, Rahul; Mikhail, Andrew; Zhuang, Yumei; Tyagi, Ethika; Zhang, Qing; Lee, Jae-Hyung; Morselli, Marco; Orozco, Luz; Guo, Weilong; Kilts, Tina M; Zhu, Jun; Zhang, Bin; Pellegrini, Matteo; Xiao, Xinshu; Young, Marian F; Gomez-Pinilla, Fernando; Yang, Xia

    2016-05-01

    Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient-host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control) and hippocampus (cognitive processing) from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  8. Personality and complex brain networks: The role of openness to experience in default network efficiency

    OpenAIRE

    Beaty, Roger E.; Kaufman, Scott Barry; Benedek, Mathias; Jung, Rex E.; Kenett, Yoed N.; Jauk, Emanuel; Neubauer, Aljoscha C.; Silvia, Paul J.

    2015-01-01

    Abstract The brain's default network (DN) has been a topic of considerable empirical interest. In fMRI research, DN activity is associated with spontaneous and self?generated cognition, such as mind?wandering, episodic memory retrieval, future thinking, mental simulation, theory of mind reasoning, and creative cognition. Despite large literatures on developmental and disease?related influences on the DN, surprisingly little is known about the factors that impact normal variation in DN functio...

  9. The Impact of Reading Intervention on Brain Responses Underlying Language in Children With Autism.

    Science.gov (United States)

    Murdaugh, Donna L; Deshpande, Hrishikesh D; Kana, Rajesh K

    2016-01-01

    Deficits in language comprehension have been widely reported in children with autism spectrum disorders (ASD), with behavioral and neuroimaging studies finding increased reliance on visuospatial processing to aid in language comprehension. However, no study to date, has taken advantage of this strength in visuospatial processing to improve language comprehension difficulties in ASD. This study used a translational neuroimaging approach to test the role of a visual imagery-based reading intervention in improving the brain circuitry underlying language processing in children with ASD. Functional magnetic resonance imaging (MRI), in a longitudinal study design, was used to investigate intervention-related change in sentence comprehension, brain activation, and functional connectivity in three groups of participants (age 8-13 years): an experimental group of ASD children (ASD-EXP), a wait-list control group of ASD children (ASD-WLC), and a group of typically developing control children. After intervention, the ASD-EXP group showed significant increase in activity in visual and language areas and right-hemisphere language area homologues, putamen, and thalamus, suggestive of compensatory routes to increase proficiency in reading comprehension. Additionally, ASD children who had the most improvement in reading comprehension after intervention showed greater functional connectivity between left-hemisphere language areas, the middle temporal gyrus and inferior frontal gyrus while reading high imagery sentences. Thus, the findings of this study, which support the principles of dual coding theory [Paivio 2007], suggest the potential of a strength-based reading intervention in changing brain responses and facilitating better reading comprehension in ASD children. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

  10. Multi-Lingual Deep Neural Networks for Language Recognition

    Science.gov (United States)

    2016-08-08

    technique to artificially add phono- tactic variability to speech for example to account for formal and informal versions of language dialect (see [4...Switchboard English shows the impact of language se- lection and the amount of training data on overall BN-DNN perfor- mance. Index Terms: language recognition...low dimensional representation of a waveform that contains speaker, language , session and channel information . With a sufficient number of recorded

  11. A Bayesian network meta-analysis of whole brain radiotherapy and stereotactic radiotherapy for brain metastasis.

    Science.gov (United States)

    Yuan, Xi; Liu, Wen-Jie; Li, Bing; Shen, Ze-Tian; Shen, Jun-Shu; Zhu, Xi-Xu

    2017-08-01

    This study was conducted to compare the effects of whole brain radiotherapy (WBRT) and stereotactic radiotherapy (SRS) in treatment of brain metastasis.A systematical retrieval in PubMed and Embase databases was performed for relative literatures on the effects of WBRT and SRS in treatment of brain metastasis. A Bayesian network meta-analysis was performed by using the ADDIS software. The effect sizes included odds ratio (OR) and 95% confidence interval (CI). A random effects model was used for the pooled analysis for all the outcome measures, including 1-year distant control rate, 1-year local control rate, 1-year survival rate, and complication. The consistency was tested by using node-splitting analysis and inconsistency standard deviation. The convergence was estimated according to the Brooks-Gelman-Rubin method.A total of 12 literatures were included in this meta-analysis. WBRT + SRS showed higher 1-year distant control rate than SRS. WBRT + SRS was better for the 1-year local control rate than WBRT. SRS and WBRT + SRS had higher 1-year survival rate than the WBRT. In addition, there was no difference in complication among the three therapies.Comprehensively, WBRT + SRS might be the choice of treatment for brain metastasis.

  12. Prereader to beginning reader: changes induced by reading acquisition in print and speech brain networks.

    Science.gov (United States)

    Chyl, Katarzyna; Kossowski, Bartosz; Dębska, Agnieszka; Łuniewska, Magdalena; Banaszkiewicz, Anna; Żelechowska, Agata; Frost, Stephen J; Mencl, William Einar; Wypych, Marek; Marchewka, Artur; Pugh, Kenneth R; Jednoróg, Katarzyna

    2018-01-01

    Literacy acquisition is a demanding process that induces significant changes in the brain, especially in the spoken and written language networks. Nevertheless, large-scale paediatric fMRI studies are still limited. We analyzed fMRI data to show how individual differences in reading performance correlate with brain activation for speech and print in 111 children attending kindergarten or first grade and examined group differences between a matched subset of emergent-readers and prereaders. Across the entire cohort, individual differences analysis revealed that reading skill was positively correlated with the magnitude of activation difference between words and symbol strings in left superior temporal, inferior frontal and fusiform gyri. Group comparisons of the matched subset of pre- and emergent-readers showed higher activity for emergent-readers in left inferior frontal, precentral, and postcentral gyri. Individual differences in activation for natural versus vocoded speech were also positively correlated with reading skill, primarily in the left temporal cortex. However, in contrast to studies on adult illiterates, group comparisons revealed higher activity in prereaders compared to readers in the frontal lobes. Print-speech coactivation was observed only in readers and individual differences analyses revealed a positive correlation between convergence and reading skill in the left superior temporal sulcus. These results emphasise that a child's brain undergoes several modifications to both visual and oral language systems in the process of learning to read. They also suggest that print-speech convergence is a hallmark of acquiring literacy. © 2017 Association for Child and Adolescent Mental Health.

  13. What language is the language-ready brain ready for?. Comment on "Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain" by Michael A. Arbib

    Science.gov (United States)

    Croft, William

    2016-03-01

    Arbib's computational comparative neuroprimatology [1] is a welcome model for cognitive linguists, that is, linguists who ground their models of language in human cognition and language use in social interaction. Arbib argues that language emerged via biological and cultural coevolution [1]; linguistic knowledge is represented by constructions, and semantic representations of linguistic constructions are grounded in embodied perceptual-motor schemas (the mirror system hypothesis). My comments offer some refinements from a linguistic point of view.

  14. Bayesian exponential random graph modeling of whole-brain structural networks across lifespan

    OpenAIRE

    Sinke, Michel R T; Dijkhuizen, Rick M; Caimo, Alberto; Stam, Cornelis J; Otte, Wim

    2016-01-01

    Descriptive neural network analyses have provided important insights into the organization of structural and functional networks in the human brain. However, these analyses have limitations for inter-subject or between-group comparisons in which network sizes and edge densities may differ, such as in studies on neurodevelopment or brain diseases. Furthermore, descriptive neural network analyses lack an appropriate generic null model and a unifying framework. These issues may be solved with an...

  15. Personality and complex brain networks: The role of openness to experience in default network efficiency.

    Science.gov (United States)

    Beaty, Roger E; Kaufman, Scott Barry; Benedek, Mathias; Jung, Rex E; Kenett, Yoed N; Jauk, Emanuel; Neubauer, Aljoscha C; Silvia, Paul J

    2016-02-01

    The brain's default network (DN) has been a topic of considerable empirical interest. In fMRI research, DN activity is associated with spontaneous and self-generated cognition, such as mind-wandering, episodic memory retrieval, future thinking, mental simulation, theory of mind reasoning, and creative cognition. Despite large literatures on developmental and disease-related influences on the DN, surprisingly little is known about the factors that impact normal variation in DN functioning. Using structural equation modeling and graph theoretical analysis of resting-state fMRI data, we provide evidence that Openness to Experience-a normally distributed personality trait reflecting a tendency to engage in imaginative, creative, and abstract cognitive processes-underlies efficiency of information processing within the DN. Across two studies, Openness predicted the global efficiency of a functional network comprised of DN nodes and corresponding edges. In Study 2, Openness remained a robust predictor-even after controlling for intelligence, age, gender, and other personality variables-explaining 18% of the variance in DN functioning. These findings point to a biological basis of Openness to Experience, and suggest that normally distributed personality traits affect the intrinsic architecture of large-scale brain systems. Hum Brain Mapp 37:773-779, 2016. © 2015 Wiley Periodicals, Inc. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  16. Second Language Word Learning through Repetition and Imitation: Functional Networks as a Function of Learning Phase and Language Distance.

    Science.gov (United States)

    Ghazi-Saidi, Ladan; Ansaldo, Ana Ines

    2017-01-01

    Introduction and Aim : Repetition and imitation are among the oldest second language (L2) teaching approaches and are frequently used in the context of L2 learning and language therapy, despite some heavy criticism. Current neuroimaging techniques allow the neural mechanisms underlying repetition and imitation to be examined. This fMRI study examines the influence of verbal repetition and imitation on network configuration. Integration changes within and between the cognitive control and language networks were studied, in a pair of linguistically close languages (Spanish and French), and compared to our previous work on a distant language pair (Ghazi-Saidi et al., 2013). Methods : Twelve healthy native Spanish-speaking (L1) adults, and 12 healthy native Persian-speaking adults learned 130 new French (L2) words, through a computerized audiovisual repetition and imitation program. The program presented colored photos of objects. Participants were instructed to look at each photo and pronounce its name as closely as possible to the native template (imitate). Repetition was encouraged as many times as necessary to learn the object's name; phonological cues were provided if necessary. Participants practiced for 15 min, over 30 days, and were tested while naming the same items during fMRI scanning, at week 1 (shallow learning phase) and week 4 (consolidation phase) of training. To compare this set of data with our previous work on Persian speakers, a similar data analysis plan including accuracy rates (AR), response times (RT), and functional integration values for the language and cognitive control network at each measure point was included, with further L1-L2 direct comparisons across the two populations. Results and Discussion : The evidence shows that learning L2 words through repetition induces neuroplasticity at the network level. Specifically, L2 word learners showed increased network integration after 3 weeks of training, with both close and distant language

  17. Second Language Word Learning through Repetition and Imitation: Functional Networks as a Function of Learning Phase and Language Distance

    Science.gov (United States)

    Ghazi-Saidi, Ladan; Ansaldo, Ana Ines

    2017-01-01

    Introduction and Aim: Repetition and imitation are among the oldest second language (L2) teaching approaches and are frequently used in the context of L2 learning and language therapy, despite some heavy criticism. Current neuroimaging techniques allow the neural mechanisms underlying repetition and imitation to be examined. This fMRI study examines the influence of verbal repetition and imitation on network configuration. Integration changes within and between the cognitive control and language networks were studied, in a pair of linguistically close languages (Spanish and French), and compared to our previous work on a distant language pair (Ghazi-Saidi et al., 2013). Methods: Twelve healthy native Spanish-speaking (L1) adults, and 12 healthy native Persian-speaking adults learned 130 new French (L2) words, through a computerized audiovisual repetition and imitation program. The program presented colored photos of objects. Participants were instructed to look at each photo and pronounce its name as closely as possible to the native template (imitate). Repetition was encouraged as many times as necessary to learn the object’s name; phonological cues were provided if necessary. Participants practiced for 15 min, over 30 days, and were tested while naming the same items during fMRI scanning, at week 1 (shallow learning phase) and week 4 (consolidation phase) of training. To compare this set of data with our previous work on Persian speakers, a similar data analysis plan including accuracy rates (AR), response times (RT), and functional integration values for the language and cognitive control network at each measure point was included, with further L1-L2 direct comparisons across the two populations. Results and Discussion: The evidence shows that learning L2 words through repetition induces neuroplasticity at the network level. Specifically, L2 word learners showed increased network integration after 3 weeks of training, with both close and distant language pairs

  18. Energy landscape analysis of the subcortical brain network unravels system properties beneath resting state dynamics.

    Science.gov (United States)

    Kang, Jiyoung; Pae, Chongwon; Park, Hae-Jeong

    2017-04-01

    The configuration of the human brain system at rest, which is in a transitory phase among multistable states, remains unknown. To investigate the dynamic systems properties of the human brain at rest, we constructed an energy landscape for the state dynamics of the subcortical brain network, a critical center that modulates whole brain states, using resting state fMRI. We evaluated alterations in energy landscapes following perturbation in network parameters, which revealed characteristics of the state dynamics in the subcortical brain system, such as maximal number of attractors, unequal temporal occupations, and readiness for reconfiguration of the system. Perturbation in the network parameters, even those as small as the ones in individual nodes or edges, caused a significant shift in the energy landscape of brain systems. The effect of the perturbation on the energy landscape depended on the network properties of the perturbed nodes and edges, with greater effects on hub nodes and hubs-connecting edges in the subcortical brain system. Two simultaneously perturbed nodes produced perturbation effects showing low sensitivity in the interhemispheric homologous nodes and strong dependency on the more primary node among the two. This study demonstrated that energy landscape analysis could be an important tool to investigate alterations in brain networks that may underlie certain brain diseases, or diverse brain functions that may emerge due to the reconfiguration of the default brain network at rest. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

    Science.gov (United States)

    Agnati, Luigi F; Marcoli, Manuela; Maura, Guido; Woods, Amina; Guidolin, Diego

    2018-02-09

    Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

  20. Still a bridge too far? Biolinguistic questions for grounding language on brains

    Science.gov (United States)

    Piattelli-Palmarini, Massimo; Uriagereka, Juan

    2008-12-01

    In this paper we discuss how Fibonacci growth patterns are apparent in the structure of human language. We moreover show how familiar dynamics yielding these sorts of patterns in nature may be taken to apply, at some level of abstraction, for the human faculty of language. The overall picture casts doubts on any simplistic treatment of language behavior, of the sort stemming from classical behaviorism in psychology (which is again popular in contemporary computational models). Instead, it appears to be more profitable to study language as a complex dynamic system, emerging in human brains for physical reasons which are yet to be fully comprehended, but which in the end disfavor any dualistic approach to the study of mind in general, and the human mind in particular.

  1. On the Relationship between Brain Laterality and Language Proficiency in L2: A Replication Study

    Directory of Open Access Journals (Sweden)

    Nima Shakouri

    2016-06-01

    Full Text Available The present paper attempted to investigate whether there is any significant relationship between participants' brain laterality and L2 proficiency level. To carry out the experiment, 30 participants administered in the present study. Fifteen of them did not have any English language learning experience and were at the start of language learning, while the rest had attended L2 learning classes for about 2 years in a popular English language center, located in Bandar-e Anzali, Iran. Finally, the researchers concluded that the activity of the right hemisphere went up by the increase in language proficiency among bilinguals. Thereupon, the result of the paper was at variance with Albert and Obler's (1978 early work on hemispheric differentiation, which indicated that bilinguals were less hemispheric dominant than monolinguals.

  2. Driving and driven architectures of directed small-world human brain functional networks.

    Directory of Open Access Journals (Sweden)

    Chaogan Yan

    Full Text Available Recently, increasing attention has been focused on the investigation of the human brain connectome that describes the patterns of structural and functional connectivity networks of the human brain. Many studies of the human connectome have demonstrated that the brain network follows a small-world topology with an intrinsically cohesive modular structure and includes several network hubs in the medial parietal regions. However, most of these studies have only focused on undirected connections between regions in which the directions of information flow are not taken into account. How the brain regions causally influence each other and how the directed network of human brain is topologically organized remain largely unknown. Here, we applied linear multivariate Granger causality analysis (GCA and graph theoretical approaches to a resting-state functional MRI dataset with a large cohort of young healthy participants (n = 86 to explore connectivity patterns of the population-based whole-brain functional directed network. This directed brain network exhibited prominent small-world properties, which obviously improved previous results of functional MRI studies showing weak small-world properties in the directed brain networks in terms of a kernel-based GCA and individual analysis. This brain network also showed significant modular structures associated with 5 well known subsystems: fronto-parietal, visual, paralimbic/limbic, subcortical and primary systems. Importantly, we identified several driving hubs predominantly located in the components of the attentional network (e.g., the inferior frontal gyrus, supplementary motor area, insula and fusiform gyrus and several driven hubs predominantly located in the components of the default mode network (e.g., the precuneus, posterior cingulate gyrus, medial prefrontal cortex and inferior parietal lobule. Further split-half analyses indicated that our results were highly reproducible between two

  3. Hierarchical brain networks active in approach and avoidance goal pursuit

    Directory of Open Access Journals (Sweden)

    Jeffrey Martin Spielberg

    2013-06-01

    Full Text Available Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal pursuit processes (e.g., motivation has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity vital to goal pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

  4. Post-concussive complaints after mild traumatic brain injury associated with altered brain networks during working memory performance

    NARCIS (Netherlands)

    van der Horn, Harm J.; Liemburg, Edith J.; Scheenen, Myrthe E.; de Koning, Myrthe E.; Spikman, Jacoba M.; van der Naalt, Joukje

    2016-01-01

    The aim was to investigate brain network function during working memory (WM) task performance in patients with uncomplicated mild traumatic brain injury (mTBI) in the sub-acute phase post-injury. We were particularly interested in differences between patients with (PCC-present) and without

  5. Using stochastic language models (SLM) to map lexical, syntactic, and phonological information processing in the brain.

    Science.gov (United States)

    Lopopolo, Alessandro; Frank, Stefan L; van den Bosch, Antal; Willems, Roel M

    2017-01-01

    Language comprehension involves the simultaneous processing of information at the phonological, syntactic, and lexical level. We track these three distinct streams of information in the brain by using stochastic measures derived from computational language models to detect neural correlates of phoneme, part-of-speech, and word processing in an fMRI experiment. Probabilistic language models have proven to be useful tools for studying how language is processed as a sequence of symbols unfolding in time. Conditional probabilities between sequences of words are at the basis of probabilistic measures such as surprisal and perplexity which have been successfully used as predictors of several behavioural and neural correlates of sentence processing. Here we computed perplexity from sequences of words and their parts of speech, and their phonemic transcriptions. Brain activity time-locked to each word is regressed on the three model-derived measures. We observe that the brain keeps track of the statistical structure of lexical, syntactic and phonological information in distinct areas.

  6. Exploring brain functional plasticity in world class gymnasts: a network analysis.

    Science.gov (United States)

    Wang, Junjing; Lu, Min; Fan, Yuanyuan; Wen, Xue; Zhang, Ruibin; Wang, Bin; Ma, Qing; Song, Zheng; He, Yong; Wang, Jun; Huang, Ruiwang

    2016-09-01

    Long-term motor skill learning can induce plastic structural and functional reorganization of the brain. Our previous studies detected brain structural plasticity related to long-term intensive gymnastic training in world class gymnasts (WCGs). The goal of this study was to investigate brain functional plasticity in WCGs by using network measures of brain functional networks. Specifically, we acquired resting-state fMRI data from 13 WCGs and 14 controls, constructed their brain functional networks, and compared the differences in their network parameters. At the whole brain level, we detected significantly decreased overall functional connectivity (FC) and decreased local and global efficiency in the WCGs compared to the controls. At the modular level, we found intra- and inter-modular reorganization in three modules, the cerebellum, the cingulo-opercular and fronto-parietal networks, in the WCGs. On the nodal level, we revealed significantly decreased nodal strength and efficiency in several non-rich club regions of these three modules in the WCGs. These results suggested that functional plasticity can be detected in the brain functional networks of WCGs, especially in the cerebellum, fronto-parietal network, and cingulo-opercular network. In addition, we found that the FC between the fronto-parietal network and the sensorimotor network was significantly negatively correlated with the number of years of training in the WCGs. These findings may help us to understand the outstanding gymnastic performance of the gymnasts and to reveal the neural mechanisms that distinguish WCGs from controls.

  7. Can You Hear Me Now? Musical Training Shapes Functional Brain Networks for Selective Auditory Attention and Hearing Speech in Noise

    Science.gov (United States)

    Strait, Dana L.; Kraus, Nina

    2011-01-01

    Even in the quietest of rooms, our senses are perpetually inundated by a barrage of sounds, requiring the auditory system to adapt to a variety of listening conditions in order to extract signals of interest (e.g., one speaker's voice amidst others). Brain networks that promote selective attention are thought to sharpen the neural encoding of a target signal, suppressing competing sounds and enhancing perceptual performance. Here, we ask: does musical training benefit cortical mechanisms that underlie selective attention to speech? To answer this question, we assessed the impact of selective auditory attention on cortical auditory-evoked response variability in musicians and non-musicians. Outcomes indicate strengthened brain networks for selective auditory attention in musicians in that musicians but not non-musicians demonstrate decreased prefrontal response variability with auditory attention. Results are interpreted in the context of previous work documenting perceptual and subcortical advantages in musicians for the hearing and neural encoding of speech in background noise. Musicians’ neural proficiency for selectively engaging and sustaining auditory attention to language indicates a potential benefit of music for auditory training. Given the importance of auditory attention for the development and maintenance of language-related skills, musical training may aid in the prevention, habilitation, and remediation of individuals with a wide range of attention-based language, listening and learning impairments. PMID:21716636

  8. Can you hear me now? Musical training shapes functional brain networks for selective auditory attention and hearing speech in noise

    Directory of Open Access Journals (Sweden)

    Dana L Strait

    2011-06-01

    Full Text Available Even in the quietest of rooms, our senses are perpetually inundated by a barrage of sounds, requiring the auditory system to adapt to a variety of listening conditions in order to extract signals of interest (e.g., one speaker’s voice amidst others. Brain networks that promote selective attention are thought to sharpen the neural encoding of a target signal, suppressing competing sounds and enhancing perceptual performance. Here, we ask: does musical training benefit cortical mechanisms that underlie selective attention to speech? To answer this question, we assessed the impact of selective auditory attention on cortical auditory-evoked response variability in musicians and nonmusicians. Outcomes indicate strengthened brain networks for selective auditory attention in musicians in that musicians but not nonmusicians demonstrate decreased prefrontal response variability with auditory attention. Results are interpreted in the context of previous work from our laboratory documenting perceptual and subcortical advantages in musicians for the hearing and neural encoding of speech in background noise. Musicians’ neural proficiency for selectively engaging and sustaining auditory attention to language indicates a potential benefit of music for auditory training. Given the importance of auditory attention for the development of language-related skills, musical training may aid in the prevention, habilitation and remediation of children with a wide range of attention-based language and learning impairments.

  9. Can you hear me now? Musical training shapes functional brain networks for selective auditory attention and hearing speech in noise.

    Science.gov (United States)

    Strait, Dana L; Kraus, Nina

    2011-01-01

    Even in the quietest of rooms, our senses are perpetually inundated by a barrage of sounds, requiring the auditory system to adapt to a variety of listening conditions in order to extract signals of interest (e.g., one speaker's voice amidst others). Brain networks that promote selective attention are thought to sharpen the neural encoding of a target signal, suppressing competing sounds and enhancing perceptual performance. Here, we ask: does musical training benefit cortical mechanisms that underlie selective attention to speech? To answer this question, we assessed the impact of selective auditory attention on cortical auditory-evoked response variability in musicians and non-musicians. Outcomes indicate strengthened brain networks for selective auditory attention in musicians in that musicians but not non-musicians demonstrate decreased prefrontal response variability with auditory attention. Results are interpreted in the context of previous work documenting perceptual and subcortical advantages in musicians for the hearing and neural encoding of speech in background noise. Musicians' neural proficiency for selectively engaging and sustaining auditory attention to language indicates a potential benefit of music for auditory training. Given the importance of auditory attention for the development and maintenance of language-related skills, musical training may aid in the prevention, habilitation, and remediation of individuals with a wide range of attention-based language, listening and learning impairments.

  10. L2-Proficiency-Dependent Laterality Shift in Structural Connectivity of Brain Language Pathways.

    Science.gov (United States)

    Xiang, Huadong; van Leeuwen, Tessa Marije; Dediu, Dan; Roberts, Leah; Norris, David G; Hagoort, Peter

    2015-08-01

    Diffusion tensor imaging (DTI) and a longitudinal language learning approach were applied to investigate the relationship between the achieved second language (L2) proficiency during L2 learning and the reorganization of structural connectivity between core language areas. Language proficiency tests and DTI scans were obtained from German students before and after they completed an intensive 6-week course of the Dutch language. In the initial learning stage, with increasing L2 proficiency, the hemispheric dominance of the Brodmann area (BA) 6-temporal pathway (mainly along the arcuate fasciculus) shifted from the left to the right hemisphere. With further increased proficiency, however, lateralization dominance was again found in the left BA6-temporal pathway. This result is consistent with reports in the literature that imply a stronger involvement of the right hemisphere in L2 processing especially for less proficient L2 speakers. This is the first time that an L2 proficiency-dependent laterality shift in the structural connectivity of language pathways during L2 acquisition has been observed to shift from left to right and back to left hemisphere dominance with increasing L2 proficiency. The authors additionally find that changes in fractional anisotropy values after the course are related to the time elapsed between the two scans. The results suggest that structural connectivity in (at least part of) the perisylvian language network may be subject to fast dynamic changes following language learning.

  11. Domain-General Brain Regions Do Not Track Linguistic Input as Closely as Language-Selective Regions.

    Science.gov (United States)

    Blank, Idan A; Fedorenko, Evelina

    2017-10-11

    Language comprehension engages a cortical network of left frontal and temporal regions. Activity in this network is language-selective, showing virtually no modulation by nonlinguistic tasks. In addition, language comprehension engages a second network consisting of bilateral frontal, parietal, cingulate, and insular regions. Activity in this "multiple demand" (MD) network scales with comprehension difficulty, but also with cognitive effort across a wide range of nonlinguistic tasks in a domain-general fashion. Given the functional dissociation between the language and MD networks, their respective contributions to comprehension are likely distinct, yet such differences remain elusive. Prior neuroimaging studies have suggested that activity in each network covaries with some linguistic features that, behaviorally, influence on-line processing and comprehension. This sensitivity of the language and MD networks to local input characteristics has often been interpreted, implicitly or explicitly, as evidence that both networks track linguistic input closely, and in a manner consistent across individuals. Here, we used fMRI to directly test this assumption by comparing the BOLD signal time courses in each network across different people ( n = 45, men and women) listening to the same story. Language network activity showed fewer individual differences, indicative of closer input tracking, whereas MD network activity was more idiosyncratic and, moreover, showed lower reliability within an individual across repetitions of a story. These findings constrain cognitive models of language comprehension by suggesting a novel distinction between the processes implemented in the language and MD networks. SIGNIFICANCE STATEMENT Language comprehension recruits both language-specific mechanisms and domain-general mechanisms that are engaged in many cognitive processes. In the human cortex, language-selective mechanisms are implemented in the left-lateralized "core language network

  12. Differential synchronization in default and task-specific networks of the human brain

    Directory of Open Access Journals (Sweden)

    Aaron eKirschner

    2012-05-01

    Full Text Available On a regional scale the brain is organized into dynamic functional networks. The activity within one of these, the default network, can be dissociated from that in other task-specific networks. All brain networks are connected structurally, but evidently are only transiently connected functionally. One hypothesis as to how such transient functional coupling occurs is that network formation and dissolution is mediated, or at least accompanied, by increases and decreases in oscillatory synchronization between constituent brain regions. If so, then we should be able to find transient differences in intra-network synchronization between the default network and a task-specific network. In order to investigate this hypothesis we conducted two experiments in which subjects engaged in a Sustained Attention to Response Task (SART while having brain activity recorded via high-density electroencephalography (EEG. We found that during periods when attention was focused internally (mind-wandering there was significantly more neural phase synchronization between brain regions associated with the default network, whereas during periods when subjects were focused on performing the visual task there was significantly more neural phase synchrony within a task-specific brain network that shared some of the same brain regions. These differences in network synchrony occurred in each of theta, alpha, and gamma frequency bands. A similar pattern of differential oscillatory power changes, indicating modulation of local synchronization by attention state, was also found. These results provide further evidence that the human brain is intrinsically organized into default and task-specific brain networks, and confirm that oscillatory synchronization is a potential mechanism for functional coupling within these networks.

  13. Verbal ability and language outcome following traumatic brain injury in early childhood.

    Science.gov (United States)

    Crowe, Louise M; Anderson, Vicki; Barton, Sarah; Babl, Franz E; Catroppa, Cathy

    2014-01-01

    To investigate language outcomes of TBI in preschool-aged children. Competent early language skills are pivotal for the future development of literacy skills. While previous research has reported that traumatic brain injury (TBI) places children at risk of language impairments, the majority of these studies have been conducted with school-aged children. Royal Children's Hospital, Melbourne, Australia. Children aged 4 to 6 years who had sustained a mild (N = 19) or moderate/severe (N = 16) TBI prior to 3 years of age and a control group (N = 20) of typically developing children matched for age, gender, and socioeconomic status. The Wechsler Preschool and Primary School Scale of Intelligence, Third Edition, measured Verbal IQ. The Clinical Evaluation of Language Fundamentals-Preschool version and the Bus Story Test measured language skills. More severely injured children displayed greater impairments in verbal intellectual abilities and language skills compared with children with mild TBI and uninjured children. Children with mild TBI performed similarly to children in the control group. Language appears vulnerable to TBI and should be investigated as a matter of course in clinical assessments of TBI recovery.

  14. The JOYN 2.0 project social networking and language learning: some preliminary insights

    OpenAIRE

    Riordan, Elaine; James, Phil

    2012-01-01

    peer-reviewed The introduction of social networking in language learning is becoming increasingly important, and as a result, teachers require new skills in their newfound roles as moderators of informal online learning. This paper presents details about a two-year EU Lifelong Learning funded project, namely JOYN 2.0, which aims to promote language learning through social networking http://www.joynlanguages.eu/. The JOYN 2.0 projects examines the process of moderating lan...

  15. The structural and functional brain networks that support human social networks.

    Science.gov (United States)

    Noonan, M P; Mars, R B; Sallet, J; Dunbar, R I M; Fellows, L K

    2018-02-20

    Social skills rely on a specific set of cognitive processes, raising the possibility that individual differences in social networks are related to differences in specific brain structural and functional networks. Here, we tested this hypothesis with multimodality neuroimaging. With diffusion MRI (DMRI), we showed that differences in structural integrity of particular white matter (WM) tracts, including cingulum bundle, extreme capsule and arcuate fasciculus were associated with an individual's social network size (SNS). A voxel-based morphology analysis demonstrated correlations between gray matter (GM) volume and SNS in limbic and temporal lobe regions. These structural changes co-occured with functional network differences. As a function of SNS, dorsomedial and dorsolateral prefrontal cortex showed altered resting-state functional connectivity with the default mode network (DMN). Finally, we integrated these three complementary methods, interrogating the relationship between social GM clusters and specific WM and resting-state networks (RSNs). Probabilistic tractography seeded in these GM nodes utilized the SNS-related WM pathways. Further, the spatial and functional overlap between the social GM clusters and the DMN was significantly closer than other control RSNs. These integrative analyses provide convergent evidence of the role of specific circuits in SNS, likely supporting the adaptive behavior necessary for success in extensive social environments. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

  16. Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

    Science.gov (United States)

    Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

    2015-01-01

    BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas. PMID:25759649

  17. Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

    Directory of Open Access Journals (Sweden)

    Xerxes D. Arsiwalla

    2015-02-01

    Full Text Available BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for real-time exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably, due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

  18. Network dynamics with BrainX(3): a large-scale simulation of the human brain network with real-time interaction.

    Science.gov (United States)

    Arsiwalla, Xerxes D; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F M J

    2015-01-01

    BrainX(3) is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX(3) in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX(3) can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

  19. Selective vulnerability related to aging in large-scale resting brain networks.

    Science.gov (United States)

    Zhang, Hong-Ying; Chen, Wen-Xin; Jiao, Yun; Xu, Yao; Zhang, Xiang-Rong; Wu, Jing-Tao

    2014-01-01

    Normal aging is associated with cognitive decline. Evidence indicates that large-scale brain networks are affected by aging; however, it has not been established whether aging has equivalent effects on specific large-scale networks. In the present study, 40 healthy subjects including 22 older (aged 60-80 years) and 18 younger (aged 22-33 years) adults underwent resting-state functional MRI scanning. Four canonical resting-state networks, including the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN) and salience network, were extracted, and the functional connectivities in these canonical networks were compared between the younger and older groups. We found distinct, disruptive alterations present in the large-scale aging-related resting brain networks: the ECN was affected the most, followed by the DAN. However, the DMN and salience networks showed limited functional connectivity disruption. The visual network served as a control and was similarly preserved in both groups. Our findings suggest that the aged brain is characterized by selective vulnerability in large-scale brain networks. These results could help improve our understanding of the mechanism of degeneration in the aging brain. Additional work is warranted to determine whether selective alterations in the intrinsic networks are related to impairments in behavioral performance.

  20. Investigating the Use of a Smartphone Social Networking Application on Language Learning

    Science.gov (United States)

    Sung, Ko-Yin; Poole, Frederick

    2017-01-01

    This study explored college students' use of a popular smartphone social networking application, WeChat, in a tandem language learning project. The research questions included (1) How do Chinese-English dyads utilize the WeChat app for weekly language learning?, and (2) What are the perceptions of the Chinese-English dyads on the use of the WeChat…

  1. The Effectiveness of Social Media Network Telegram in Teaching English Language Pronunciation to Iranian EFL Learners

    Science.gov (United States)

    Xodabande, Ismail

    2017-01-01

    In recent years, the expansion of digital technologies, multimedia, and social networks, dramatically transformed our lives. Education in general and the area of foreign language teaching and learning have also benefited hugely from those developments and advances. As a result, the face of language learning is changing and new technologies provide…

  2. Brain signatures of early lexical and morphological learning of a new language.

    Science.gov (United States)

    Havas, Viktória; Laine, Matti; Rodríguez Fornells, Antoni

    2017-07-01

    Morphology is an important part of language processing but little is known about how adult second language learners acquire morphological rules. Using a word-picture associative learning task, we have previously shown that a brief exposure to novel words with embedded morphological structure (suffix for natural gender) is enough for language learners to acquire the hidden morphological rule. Here we used this paradigm to study the brain signatures of early morphological learning in a novel language in adults. Behavioural measures indicated successful lexical (word stem) and morphological (gender suffix) learning. A day after the learning phase, event-related brain potentials registered during a recognition memory task revealed enhanced N400 and P600 components for stem and suffix violations, respectively. An additional effect observed with combined suffix and stem violations was an enhancement of an early N2 component, most probably related to conflict-detection processes. Successful morphological learning was also evident in the ERP responses to the subsequent rule-generalization task with new stems, where violation of the morphological rule was associated with an early (250-400ms) and late positivity (750-900ms). Overall, these findings tend to converge with lexical and morphosyntactic violation effects observed in L1 processing, suggesting that even after a short exposure, adult language learners can acquire both novel words and novel morphological rules. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. Targeting Neuronal Networks with Combined Drug and Stimulation Paradigms Guided by Neuroimaging to Treat Brain Disorders.

    Science.gov (United States)

    Faingold, Carl L; Blumenfeld, Hal

    2015-10-01

    Improved therapy of brain disorders can be achieved by focusing on neuronal networks, utilizing combined pharmacological and stimulation paradigms guided by neuroimaging. Neuronal networks that mediate normal brain functions, such as hearing, interact with other networks, which is important but commonly neglected. Network interaction changes often underlie brain disorders, including epilepsy. "Conditional multireceptive" (CMR) brain areas (e.g., brainstem reticular formation and amygdala) are critical in mediating neuroplastic changes that facilitate network interactions. CMR neurons receive multiple inputs but exhibit extensive response variability due to milieu and behavioral state changes and are exquisitely sensitive to agents that increase or inhibit GABA-mediated inhibition. Enhanced CMR neuronal responsiveness leads to expression of emergent properties--nonlinear events--resulting from network self-organization. Determining brain disorder mechanisms requires animals that model behaviors and neuroanatomical substrates of human disorders identified by neuroimaging. However, not all sites activated during network operation are requisite for that operation. Other active sites are ancillary, because their blockade does not alter network function. Requisite network sites exhibit emergent properties that are critical targets for pharmacological and stimulation therapies. Improved treatment of brain disorders should involve combined pharmacological and stimulation therapies, guided by neuroimaging, to correct network malfunctions by targeting specific network neurons. © The Author(s) 2015.

  4. Graph analysis of functional brain networks: practical issues in translational neuroscience.

    Science.gov (United States)

    De Vico Fallani, Fabrizio; Richiardi, Jonas; Chavez, Mario; Achard, Sophie

    2014-10-05

    The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective, communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires the know-how of all the methodological steps of the pipeline that manipulate the input brain signals and extract the functional network properties. On the other hand, knowledge of the neural phenomenon under study is required to perform physiologically relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  5. Mood-dependent integration in discourse comprehension: happy and sad moods affect consistency processing via different brain networks.

    Science.gov (United States)

    Egidi, Giovanna; Caramazza, Alfonso

    2014-12-01

    According to recent research on language comprehension, the semantic features of a text are not the only determinants of whether incoming information is understood as consistent. Listeners' pre-existing affective states play a crucial role as well. The current fMRI experiment examines the effects of happy and sad moods during comprehension of consistent and inconsistent story endings, focusing on brain regions previously linked to two integration processes: inconsistency detection, evident in stronger responses to inconsistent endings, and fluent processing (accumulation), evident in stronger responses to consistent endings. The analysis evaluated whether differences in the BOLD response for consistent and inconsistent story endings correlated with self-reported mood scores after a mood induction procedure. Mood strongly affected regions previously associated with inconsistency detection. Happy mood increased sensitivity to inconsistency in regions specific for inconsistency detection (e.g., left IFG, left STS), whereas sad mood increased sensitivity to inconsistency in regions less specific for language processing (e.g., right med FG, right SFG). Mood affected more weakly regions involved in accumulation of information. These results show that mood can influence activity in areas mediating well-defined language processes, and highlight that integration is the result of context-dependent mechanisms. The finding that language comprehension can involve different networks depending on people's mood highlights the brain's ability to reorganize its functions. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Visual language recognition with a feed-forward network of spiking neurons

    Energy Technology Data Exchange (ETDEWEB)

    Rasmussen, Craig E [Los Alamos National Laboratory; Garrett, Kenyan [Los Alamos National Laboratory; Sottile, Matthew [GALOIS; Shreyas, Ns [INDIANA UNIV.

    2010-01-01

    An analogy is made and exploited between the recognition of visual objects and language parsing. A subset of regular languages is used to define a one-dimensional 'visual' language, in which the words are translational and scale invariant. This allows an exploration of the viewpoint invariant languages that can be solved by a network of concurrent, hierarchically connected processors. A language family is defined that is hierarchically tiling system recognizable (HREC). As inspired by nature, an algorithm is presented that constructs a cellular automaton that recognizes strings from a language in the HREC family. It is demonstrated how a language recognizer can be implemented from the cellular automaton using a feed-forward network of spiking neurons. This parser recognizes fixed-length strings from the language in parallel and as the computation is pipelined, a new string can be parsed in each new interval of time. The analogy with formal language theory allows inferences to be drawn regarding what class of objects can be recognized by visual cortex operating in purely feed-forward fashion and what class of objects requires a more complicated network architecture.

  7. Hierarchical anatomical brain networks for MCI prediction: revisiting volumetric measures.

    Directory of Open Access Journals (Sweden)

    Luping Zhou

    Full Text Available Owning to its clinical accessibility, T1-weighted MRI (Magnetic Resonance Imaging has been extensively studied in the past decades for prediction of Alzheimer's disease (AD and mild cognitive impairment (MCI. The volumes of gray matter (GM, white matter (WM and cerebrospinal fluid (CSF are the most commonly used measurements, resulting in many successful applications. It has been widely observed that disease-induced structural changes may not occur at isolated spots, but in several inter-related regions. Therefore, for better characterization of brain pathology, we propose in this paper a means to extract inter-regional correlation based features from local volumetric measurements. Specifically, our approach involves constructing an anatomical brain network for each subject, with each node representing a Region of Interest (ROI and each edge representing Pearson correlation of tissue volumetric measurements between ROI pairs. As second order volumetric measurements, network features are more descriptive but also more sensitive to noise. To overcome this limitation, a hierarchy of ROIs is used to suppress noise at different scales. Pairwise interactions are considered not only for ROIs with the same scale in the same layer of the hierarchy, but also for ROIs across different scales in different layers. To address the high dimensionality problem resulting from the large number of network features, a supervised dimensionality reduction method is further employed to embed a selected subset of features into a low dimensional feature space, while at the same time preserving discriminative information. We demonstrate with experimental results the efficacy of this embedding strategy in comparison with some other commonly used approaches. In addition, although the proposed method can be easily generalized to incorporate other metrics of regional similarities, the benefits of using Pearson correlation in our application are reinforced by the experimental

  8. Abnormal connectivity in the sensorimotor network predicts attention deficits in traumatic brain injury.

    Science.gov (United States)

    Shumskaya, Elena; van Gerven, Marcel A J; Norris, David G; Vos, Pieter E; Kessels, Roy P C

    2017-03-01

    The aim of this study was to explore modifications of functional connectivity in multiple resting-state networks (RSNs) after moderate to severe traumatic brain injury (TBI) and evaluate the relationship between functional connectivity patterns and cognitive abnormalities. Forty-three moderate/severe TBI patients and 34 healthy controls (HC) underwent resting-state fMRI. Group ICA was applied to identify RSNs. Between-subject analysis was performed using dual regression. Multiple linear regressions were used to investigate the relationship between abnormal connectivity strength and neuropsychological outcome. Forty (93%) TBI patients showed moderate disability, while 2 (5%) and 1 (2%) upper severe disability and low good recovery, respectively. TBI patients performed worse than HC on the domains attention and language. We found increased connectivity in sensorimotor, visual, default mode (DMN), executive, and cerebellar RSNs after TBI. We demonstrated an effect of connectivity in the sensorimotor RSN on attention (p < 10 -3 ) and a trend towards a significant effect of the DMN connectivity on attention (p = 0.058). A group-by-network interaction on attention was found in the sensorimotor network (p = 0.002). In TBI, attention was positively related to abnormal connectivity within the sensorimotor RSN, while in HC this relation was negative. Our results show altered patterns of functional connectivity after TBI. Attention impairments in TBI were associated with increased connectivity in the sensorimotor network. Further research is needed to test whether attention in TBI patients is directly affected by changes in functional connectivity in the sensorimotor network or whether the effect is actually driven by changes in the DMN.

  9. Morphological features of the neonatal brain support development of subsequent cognitive, language, and motor abilities.

    Science.gov (United States)

    Spann, Marisa N; Bansal, Ravi; Rosen, Tove S; Peterson, Bradley S

    2014-09-01

    Knowledge of the role of brain maturation in the development of cognitive abilities derives primarily from studies of school-age children to adults. Little is known about the morphological features of the neonatal brain that support the subsequent development of abilities in early childhood, when maturation of the brain and these abilities are the most dynamic. The goal of our study was to determine whether brain morphology during the neonatal period supports early cognitive development through 2 years of age. We correlated morphological features of the cerebral surface assessed using deformation-based measures (surface distances) of high-resolution MRI scans for 33 healthy neonates, scanned between the first to sixth week of postmenstrual life, with subsequent measures of their motor, language, and cognitive abilities at ages 6, 12, 18, and 24 months. We found that morphological features of the cerebral surface of the frontal, mesial prefrontal, temporal, and occipital regions correlated with subsequent motor scores, posterior parietal regions correlated with subsequent language scores, and temporal and occipital regions correlated with subsequent cognitive scores. Measures of the anterior and middle portions of the cingulate gyrus correlated with scores across all three domains of ability. Most of the significant findings were inverse correlations located bilaterally in the brain. The inverse correlations may suggest either that a more protracted morphological maturation or smaller local volumes of neonatal brain tissue supports better performance on measures of subsequent motor, language, and cognitive abilities throughout the first 2 years of postnatal life. The correlations of morphological measures of the cingulate with measures of performance across all domains of ability suggest that the cingulate supports a broad range of skills in infancy and early childhood, similar to its functions in older children and adults. Copyright © 2014 Wiley Periodicals, Inc.

  10. The brain's functional network architecture reveals human motives.

    Science.gov (United States)

    Hein, Grit; Morishima, Yosuke; Leiberg, Susanne; Sul, Sunhae; Fehr, Ernst

    2016-03-04

    Goal-directed human behaviors are driven by motives. Motives are, however, purely mental constructs that are not directly observable. Here, we show that the brain's functional network architecture captures information that predicts different motives behind the same altruistic act with high accuracy. In contrast, mere activity in these regions contains no information about motives. Empathy-based altruism is primarily characterized by a positive connectivity from the anterior cingulate cortex (ACC) to the anterior insula (AI), whereas reciprocity-based altruism additionally invokes strong positive connectivity from the AI to the ACC and even stronger positive connectivity from the AI to the ventral striatum. Moreover, predominantly selfish individuals show distinct functional architectures compared to altruists, and they only increase altruistic behavior in response to empathy inductions, but not reciprocity inductions. Copyright © 2016, American Association for the Advancement of Science.