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Sample records for neural language organization

  1. Delayed development of neural language organization in very preterm born children.

    Science.gov (United States)

    Mürner-Lavanchy, Ines; Steinlin, Maja; Kiefer, Claus; Weisstanner, Christian; Ritter, Barbara Catherine; Perrig, Walter; Everts, Regula

    2014-01-01

    This study investigates neural language organization in very preterm born children compared to control children and examines the relationship between language organization, age, and language performance. Fifty-six preterms and 38 controls (7-12 y) completed a functional magnetic resonance imaging language task. Lateralization and signal change were computed for language-relevant brain regions. Younger preterms showed a bilateral language network whereas older preterms revealed left-sided language organization. No age-related differences in language organization were observed in controls. Results indicate that preterms maintain atypical bilateral language organization longer than term born controls. This might reflect a delay of neural language organization due to very premature birth.

  2. Learning to read words in a new language shapes the neural organization of the prior languages.

    Science.gov (United States)

    Mei, Leilei; Xue, Gui; Lu, Zhong-Lin; Chen, Chuansheng; Zhang, Mingxia; He, Qinghua; Wei, Miao; Dong, Qi

    2014-12-01

    Learning a new language entails interactions with one׳s prior language(s). Much research has shown how native language affects the cognitive and neural mechanisms of a new language, but little is known about whether and how learning a new language shapes the neural mechanisms of prior language(s). In two experiments in the current study, we used an artificial language training paradigm in combination with an fMRI to examine (1) the effects of different linguistic components (phonology and semantics) of a new language on the neural process of prior languages (i.e., native and second languages), and (2) whether such effects were modulated by the proficiency level in the new language. Results of Experiment 1 showed that when the training in a new language involved semantics (as opposed to only visual forms and phonology), neural activity during word reading in the native language (Chinese) was reduced in several reading-related regions, including the left pars opercularis, pars triangularis, bilateral inferior temporal gyrus, fusiform gyrus, and inferior occipital gyrus. Results of Experiment 2 replicated the results of Experiment 1 and further found that semantic training also affected neural activity during word reading in the subjects׳ second language (English). Furthermore, we found that the effects of the new language were modulated by the subjects׳ proficiency level in the new language. These results provide critical imaging evidence for the influence of learning to read words in a new language on word reading in native and second languages. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Neural Language Processing in Adolescent First-Language Learners: Longitudinal Case Studies in American Sign Language.

    Science.gov (United States)

    Ferjan Ramirez, Naja; Leonard, Matthew K; Davenport, Tristan S; Torres, Christina; Halgren, Eric; Mayberry, Rachel I

    2016-03-01

    One key question in neurolinguistics is the extent to which the neural processing system for language requires linguistic experience during early life to develop fully. We conducted a longitudinal anatomically constrained magnetoencephalography (aMEG) analysis of lexico-semantic processing in 2 deaf adolescents who had no sustained language input until 14 years of age, when they became fully immersed in American Sign Language. After 2 to 3 years of language, the adolescents' neural responses to signed words were highly atypical, localizing mainly to right dorsal frontoparietal regions and often responding more strongly to semantically primed words (Ferjan Ramirez N, Leonard MK, Torres C, Hatrak M, Halgren E, Mayberry RI. 2014. Neural language processing in adolescent first-language learners. Cereb Cortex. 24 (10): 2772-2783). Here, we show that after an additional 15 months of language experience, the adolescents' neural responses remained atypical in terms of polarity. While their responses to less familiar signed words still showed atypical localization patterns, the localization of responses to highly familiar signed words became more concentrated in the left perisylvian language network. Our findings suggest that the timing of language experience affects the organization of neural language processing; however, even in adolescence, language representation in the human brain continues to evolve with experience. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  4. How sensory-motor systems impact the neural organization for language: direct contrasts between spoken and signed language

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    Emmorey, Karen; McCullough, Stephen; Mehta, Sonya; Grabowski, Thomas J.

    2014-01-01

    To investigate the impact of sensory-motor systems on the neural organization for language, we conducted an H215O-PET study of sign and spoken word production (picture-naming) and an fMRI study of sign and audio-visual spoken language comprehension (detection of a semantically anomalous sentence) with hearing bilinguals who are native users of American Sign Language (ASL) and English. Directly contrasting speech and sign production revealed greater activation in bilateral parietal cortex for signing, while speaking resulted in greater activation in bilateral superior temporal cortex (STC) and right frontal cortex, likely reflecting auditory feedback control. Surprisingly, the language production contrast revealed a relative increase in activation in bilateral occipital cortex for speaking. We speculate that greater activation in visual cortex for speaking may actually reflect cortical attenuation when signing, which functions to distinguish self-produced from externally generated visual input. Directly contrasting speech and sign comprehension revealed greater activation in bilateral STC for speech and greater activation in bilateral occipital-temporal cortex for sign. Sign comprehension, like sign production, engaged bilateral parietal cortex to a greater extent than spoken language. We hypothesize that posterior parietal activation in part reflects processing related to spatial classifier constructions in ASL and that anterior parietal activation may reflect covert imitation that functions as a predictive model during sign comprehension. The conjunction analysis for comprehension revealed that both speech and sign bilaterally engaged the inferior frontal gyrus (with more extensive activation on the left) and the superior temporal sulcus, suggesting an invariant bilateral perisylvian language system. We conclude that surface level differences between sign and spoken languages should not be dismissed and are critical for understanding the neurobiology of language

  5. Self-organizing map models of language acquisition

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    Li, Ping; Zhao, Xiaowei

    2013-01-01

    Connectionist models have had a profound impact on theories of language. While most early models were inspired by the classic parallel distributed processing architecture, recent models of language have explored various other types of models, including self-organizing models for language acquisition. In this paper, we aim at providing a review of the latter type of models, and highlight a number of simulation experiments that we have conducted based on these models. We show that self-organizing connectionist models can provide significant insights into long-standing debates in both monolingual and bilingual language development. We suggest future directions in which these models can be extended, to better connect with behavioral and neural data, and to make clear predictions in testing relevant psycholinguistic theories. PMID:24312061

  6. Do neural nets learn statistical laws behind natural language?

    Directory of Open Access Journals (Sweden)

    Shuntaro Takahashi

    Full Text Available The performance of deep learning in natural language processing has been spectacular, but the reasons for this success remain unclear because of the inherent complexity of deep learning. This paper provides empirical evidence of its effectiveness and of a limitation of neural networks for language engineering. Precisely, we demonstrate that a neural language model based on long short-term memory (LSTM effectively reproduces Zipf's law and Heaps' law, two representative statistical properties underlying natural language. We discuss the quality of reproducibility and the emergence of Zipf's law and Heaps' law as training progresses. We also point out that the neural language model has a limitation in reproducing long-range correlation, another statistical property of natural language. This understanding could provide a direction for improving the architectures of neural networks.

  7. Neural systems supporting linguistic structure, linguistic experience, and symbolic communication in sign language and gesture.

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    Newman, Aaron J; Supalla, Ted; Fernandez, Nina; Newport, Elissa L; Bavelier, Daphne

    2015-09-15

    Sign languages used by deaf communities around the world possess the same structural and organizational properties as spoken languages: In particular, they are richly expressive and also tightly grammatically constrained. They therefore offer the opportunity to investigate the extent to which the neural organization for language is modality independent, as well as to identify ways in which modality influences this organization. The fact that sign languages share the visual-manual modality with a nonlinguistic symbolic communicative system-gesture-further allows us to investigate where the boundaries lie between language and symbolic communication more generally. In the present study, we had three goals: to investigate the neural processing of linguistic structure in American Sign Language (using verbs of motion classifier constructions, which may lie at the boundary between language and gesture); to determine whether we could dissociate the brain systems involved in deriving meaning from symbolic communication (including both language and gesture) from those specifically engaged by linguistically structured content (sign language); and to assess whether sign language experience influences the neural systems used for understanding nonlinguistic gesture. The results demonstrated that even sign language constructions that appear on the surface to be similar to gesture are processed within the left-lateralized frontal-temporal network used for spoken languages-supporting claims that these constructions are linguistically structured. Moreover, although nonsigners engage regions involved in human action perception to process communicative, symbolic gestures, signers instead engage parts of the language-processing network-demonstrating an influence of experience on the perception of nonlinguistic stimuli.

  8. Neural bases of congenital amusia in tonal language speakers.

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    Zhang, Caicai; Peng, Gang; Shao, Jing; Wang, William S-Y

    2017-03-01

    Congenital amusia is a lifelong neurodevelopmental disorder of fine-grained pitch processing. In this fMRI study, we examined the neural bases of congenial amusia in speakers of a tonal language - Cantonese. Previous studies on non-tonal language speakers suggest that the neural deficits of congenital amusia lie in the music-selective neural circuitry in the right inferior frontal gyrus (IFG). However, it is unclear whether this finding can generalize to congenital amusics in tonal languages. Tonal language experience has been reported to shape the neural processing of pitch, which raises the question of how tonal language experience affects the neural bases of congenital amusia. To investigate this question, we examined the neural circuitries sub-serving the processing of relative pitch interval in pitch-matched Cantonese level tone and musical stimuli in 11 Cantonese-speaking amusics and 11 musically intact controls. Cantonese-speaking amusics exhibited abnormal brain activities in a widely distributed neural network during the processing of lexical tone and musical stimuli. Whereas the controls exhibited significant activation in the right superior temporal gyrus (STG) in the lexical tone condition and in the cerebellum regardless of the lexical tone and music conditions, no activation was found in the amusics in those regions, which likely reflects a dysfunctional neural mechanism of relative pitch processing in the amusics. Furthermore, the amusics showed abnormally strong activation of the right middle frontal gyrus and precuneus when the pitch stimuli were repeated, which presumably reflect deficits of attending to repeated pitch stimuli or encoding them into working memory. No significant group difference was found in the right IFG in either the whole-brain analysis or region-of-interest analysis. These findings imply that the neural deficits in tonal language speakers might differ from those in non-tonal language speakers, and overlap partly with the

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

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    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.

  10. Neural organization of linguistic short-term memory is sensory modality-dependent: evidence from signed and spoken language.

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    Pa, Judy; Wilson, Stephen M; Pickell, Herbert; Bellugi, Ursula; Hickok, Gregory

    2008-12-01

    Despite decades of research, there is still disagreement regarding the nature of the information that is maintained in linguistic short-term memory (STM). Some authors argue for abstract phonological codes, whereas others argue for more general sensory traces. We assess these possibilities by investigating linguistic STM in two distinct sensory-motor modalities, spoken and signed language. Hearing bilingual participants (native in English and American Sign Language) performed equivalent STM tasks in both languages during functional magnetic resonance imaging. Distinct, sensory-specific activations were seen during the maintenance phase of the task for spoken versus signed language. These regions have been previously shown to respond to nonlinguistic sensory stimulation, suggesting that linguistic STM tasks recruit sensory-specific networks. However, maintenance-phase activations common to the two languages were also observed, implying some form of common process. We conclude that linguistic STM involves sensory-dependent neural networks, but suggest that sensory-independent neural networks may also exist.

  11. An MEG Investigation of Neural Biomarkers and Language in Nonverbal Children with Autism Spectrum Disorders

    Science.gov (United States)

    2014-09-01

    1.Lord C, Risi S, Pickles A. Trajectory of language development in autistic spectrum disorders . In: Rice M, Warren S, eds. Developmental Language...Nonverbal Children with Autism Spectrum Disorders PRINCIPAL INVESTIGATOR: Kristina McFadden CONTRACTING ORGANIZATION: University of...SUBTITLE 5a. CONTRACT NUMBER An MEG Investigation of Neural Biomarkers and Language in Nonverbal Children with Autism Spectrum Disorders 5b

  12. Comparable mechanisms for action and language: Neural systems behind intentions, goals and means

    NARCIS (Netherlands)

    Schie, H.T. van; Toni, I.; Bekkering, H.

    2006-01-01

    In this position paper we explore correspondence between neural systems for language and action starting from recent electrophysiological findings on the roles of posterior and frontal areas in goal-directed grasping actions. The paper compares the perceptual and motor organization for action and

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

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    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…

  14. Neurally and mathematically motivated architecture for language and thought.

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    Perlovsky, L I; Ilin, R

    2010-01-01

    Neural structures of interaction between thinking and language are unknown. This paper suggests a possible architecture motivated by neural and mathematical considerations. A mathematical requirement of computability imposes significant constraints on possible architectures consistent with brain neural structure and with a wealth of psychological knowledge. How language interacts with cognition. Do we think with words, or is thinking independent from language with words being just labels for decisions? Why is language learned by the age of 5 or 7, but acquisition of knowledge represented by learning to use this language knowledge takes a lifetime? This paper discusses hierarchical aspects of language and thought and argues that high level abstract thinking is impossible without language. We discuss a mathematical technique that can model the joint language-thought architecture, while overcoming previously encountered difficulties of computability. This architecture explains a contradiction between human ability for rational thoughtful decisions and irrationality of human thinking revealed by Tversky and Kahneman; a crucial role in this contradiction might be played by language. The proposed model resolves long-standing issues: how the brain learns correct words-object associations; why animals do not talk and think like people. We propose the role played by language emotionality in its interaction with thought. We relate the mathematical model to Humboldt's "firmness" of languages; and discuss possible influence of language grammar on its emotionality. Psychological and brain imaging experiments related to the proposed model are discussed. Future theoretical and experimental research is outlined.

  15. Phonological memory in sign language relies on the visuomotor neural system outside the left hemisphere language network.

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    Kanazawa, Yuji; Nakamura, Kimihiro; Ishii, Toru; Aso, Toshihiko; Yamazaki, Hiroshi; Omori, Koichi

    2017-01-01

    Sign language is an essential medium for everyday social interaction for deaf people and plays a critical role in verbal learning. In particular, language development in those people should heavily rely on the verbal short-term memory (STM) via sign language. Most previous studies compared neural activations during signed language processing in deaf signers and those during spoken language processing in hearing speakers. For sign language users, it thus remains unclear how visuospatial inputs are converted into the verbal STM operating in the left-hemisphere language network. Using functional magnetic resonance imaging, the present study investigated neural activation while bilinguals of spoken and signed language were engaged in a sequence memory span task. On each trial, participants viewed a nonsense syllable sequence presented either as written letters or as fingerspelling (4-7 syllables in length) and then held the syllable sequence for 12 s. Behavioral analysis revealed that participants relied on phonological memory while holding verbal information regardless of the type of input modality. At the neural level, this maintenance stage broadly activated the left-hemisphere language network, including the inferior frontal gyrus, supplementary motor area, superior temporal gyrus and inferior parietal lobule, for both letter and fingerspelling conditions. Interestingly, while most participants reported that they relied on phonological memory during maintenance, direct comparisons between letters and fingers revealed strikingly different patterns of neural activation during the same period. Namely, the effortful maintenance of fingerspelling inputs relative to letter inputs activated the left superior parietal lobule and dorsal premotor area, i.e., brain regions known to play a role in visuomotor analysis of hand/arm movements. These findings suggest that the dorsal visuomotor neural system subserves verbal learning via sign language by relaying gestural inputs to

  16. Recognition of sign language gestures using neural networks

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    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.

  17. Learning language with the wrong neural scaffolding: The cost of neural commitment to sounds.

    Directory of Open Access Journals (Sweden)

    Amy Sue Finn

    2013-11-01

    Full Text Available Does tuning to one’s native language explain the sensitive period for language learning? We explore the idea that tuning to (or becoming more selective for the properties of one’s native-language could result in being less open (or plastic for tuning to the properties of a new language. To explore how this might lead to the sensitive period for grammar learning, we ask if tuning to an earlier-learned aspect of language (sound structure has an impact on the neural representation of a later-learned aspect (grammar. English-speaking adults learned one of two miniature artificial languages over 4 days in the lab. Compared to English, both languages had novel grammar, but only one was comprised of novel sounds. After learning a language, participants were scanned while judging the grammaticality of sentences. Judgments were performed for the newly learned language and English. Learners of the similar-sounds language recruited regions that overlapped more with English. Learners of the distinct-sounds language, however, recruited the Superior Temporal Gyrus (STG to a greater extent, which was coactive with the Inferior Frontal Gyrus (IFG. Across learners, recruitment of IFG (but not STG predicted both learning success in tests conducted prior to the scan and grammatical judgment ability during the scan. Data suggest that adults’ difficulty learning language, especially grammar, could be due, at least in part, to the neural commitments they have made to the lower level linguistic components of their native language.

  18. Learning language with the wrong neural scaffolding: the cost of neural commitment to sounds

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    Finn, Amy S.; Hudson Kam, Carla L.; Ettlinger, Marc; Vytlacil, Jason; D'Esposito, Mark

    2013-01-01

    Does tuning to one's native language explain the “sensitive period” for language learning? We explore the idea that tuning to (or becoming more selective for) the properties of one's native-language could result in being less open (or plastic) for tuning to the properties of a new language. To explore how this might lead to the sensitive period for grammar learning, we ask if tuning to an earlier-learned aspect of language (sound structure) has an impact on the neural representation of a later-learned aspect (grammar). English-speaking adults learned one of two miniature artificial languages (MALs) over 4 days in the lab. Compared to English, both languages had novel grammar, but only one was comprised of novel sounds. After learning a language, participants were scanned while judging the grammaticality of sentences. Judgments were performed for the newly learned language and English. Learners of the similar-sounds language recruited regions that overlapped more with English. Learners of the distinct-sounds language, however, recruited the Superior Temporal Gyrus (STG) to a greater extent, which was coactive with the Inferior Frontal Gyrus (IFG). Across learners, recruitment of IFG (but not STG) predicted both learning success in tests conducted prior to the scan and grammatical judgment ability during the scan. Data suggest that adults' difficulty learning language, especially grammar, could be due, at least in part, to the neural commitments they have made to the lower level linguistic components of their native language. PMID:24273497

  19. Thought beyond language: neural dissociation of algebra and natural language.

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    Monti, Martin M; Parsons, Lawrence M; Osherson, Daniel N

    2012-08-01

    A central question in cognitive science is whether natural language provides combinatorial operations that are essential to diverse domains of thought. In the study reported here, we addressed this issue by examining the role of linguistic mechanisms in forging the hierarchical structures of algebra. In a 3-T functional MRI experiment, we showed that processing of the syntax-like operations of algebra does not rely on the neural mechanisms of natural language. Our findings indicate that processing the syntax of language elicits the known substrate of linguistic competence, whereas algebraic operations recruit bilateral parietal brain regions previously implicated in the representation of magnitude. This double dissociation argues against the view that language provides the structure of thought across all cognitive domains.

  20. 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.

  1. Neural systems language: a formal modeling language for the systematic description, unambiguous communication, and automated digital curation of neural connectivity.

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    Brown, Ramsay A; Swanson, Larry W

    2013-09-01

    Systematic description and the unambiguous communication of findings and models remain among the unresolved fundamental challenges in systems neuroscience. No common descriptive frameworks exist to describe systematically the connective architecture of the nervous system, even at the grossest level of observation. Furthermore, the accelerating volume of novel data generated on neural connectivity outpaces the rate at which this data is curated into neuroinformatics databases to synthesize digitally systems-level insights from disjointed reports and observations. To help address these challenges, we propose the Neural Systems Language (NSyL). NSyL is a modeling language to be used by investigators to encode and communicate systematically reports of neural connectivity from neuroanatomy and brain imaging. NSyL engenders systematic description and communication of connectivity irrespective of the animal taxon described, experimental or observational technique implemented, or nomenclature referenced. As a language, NSyL is internally consistent, concise, and comprehensible to both humans and computers. NSyL is a promising development for systematizing the representation of neural architecture, effectively managing the increasing volume of data on neural connectivity and streamlining systems neuroscience research. Here we present similar precedent systems, how NSyL extends existing frameworks, and the reasoning behind NSyL's development. We explore NSyL's potential for balancing robustness and consistency in representation by encoding previously reported assertions of connectivity from the literature as examples. Finally, we propose and discuss the implications of a framework for how NSyL will be digitally implemented in the future to streamline curation of experimental results and bridge the gaps among anatomists, imagers, and neuroinformatics databases. Copyright © 2013 Wiley Periodicals, Inc.

  2. Cross-Linguistic Differences in the Neural Representation of Human Language: Evidence from Users of Signed Languages

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    Corina, David P.; Lawyer, Laurel A.; Cates, Deborah

    2013-01-01

    Studies of deaf individuals who are users of signed languages have provided profound insight into the neural representation of human language. Case studies of deaf signers who have incurred left- and right-hemisphere damage have shown that left-hemisphere resources are a necessary component of sign language processing. These data suggest that, despite frank differences in the input and output modality of language, core left perisylvian regions universally serve linguistic function. Neuroimaging studies of deaf signers have generally provided support for this claim. However, more fine-tuned studies of linguistic processing in deaf signers are beginning to show evidence of important differences in the representation of signed and spoken languages. In this paper, we provide a critical review of this literature and present compelling evidence for language-specific cortical representations in deaf signers. These data lend support to the claim that the neural representation of language may show substantive cross-linguistic differences. We discuss the theoretical implications of these findings with respect to an emerging understanding of the neurobiology of language. PMID:23293624

  3. A Study of Recurrent and Convolutional Neural Networks in the Native Language Identification Task

    KAUST Repository

    Werfelmann, Robert

    2018-05-24

    Native Language Identification (NLI) is the task of predicting the native language of an author from their text written in a second language. The idea is to find writing habits that transfer from an author’s native language to their second language. Many approaches to this task have been studied, from simple word frequency analysis, to analyzing grammatical and spelling mistakes to find patterns and traits that are common between different authors of the same native language. This can be a very complex task, depending on the native language and the proficiency of the author’s second language. The most common approach that has seen very good results is based on the usage of n-gram features of words and characters. In this thesis, we attempt to extract lexical, grammatical, and semantic features from the sentences of non-native English essays using neural networks. The training and testing data was obtained from a large corpus of publicly available essays written by authors of several countries around the world. The neural network models consisted of Long Short-Term Memory and Convolutional networks using the sentences of each document as the input. Additional statistical features were generated from the text to complement the predictions of the neural networks, which were then used as feature inputs to a Support Vector Machine, making the final prediction. Results show that Long Short-Term Memory neural network can improve performance over a naive bag of words approach, but with a much smaller feature set. With more fine-tuning of neural network hyperparameters, these results will likely improve significantly.

  4. Are lexical tones musical? Native language's influence on neural response to pitch in different domains.

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    Chen, Ao; Peter, Varghese; Wijnen, Frank; Schnack, Hugo; Burnham, Denis

    2018-04-21

    Language experience shapes musical and speech pitch processing. We investigated whether speaking a lexical tone language natively modulates neural processing of pitch in language and music as well as their correlation. We tested tone language (Mandarin Chinese), and non-tone language (Dutch) listeners in a passive oddball paradigm measuring mismatch negativity (MMN) for (i) Chinese lexical tones and (ii) three-note musical melodies with similar pitch contours. For lexical tones, Chinese listeners showed a later MMN peak than the non-tone language listeners, whereas for MMN amplitude there were no significant differences between groups. Dutch participants also showed a late discriminative negativity (LDN). In the music condition two MMNs, corresponding to the two notes that differed between the standard and the deviant were found for both groups, and an LDN were found for both the Dutch and the Chinese listeners. The music MMNs were significantly right lateralized. Importantly, significant correlations were found between the lexical tone and the music MMNs for the Dutch but not the Chinese participants. The results suggest that speaking a tone language natively does not necessarily enhance neural responses to pitch either in language or in music, but that it does change the nature of neural pitch processing: non-tone language speakers appear to perceive lexical tones as musical, whereas for tone language speakers, lexical tones and music may activate different neural networks. Neural resources seem to be assigned differently for the lexical tones and for musical melodies, presumably depending on the presence or absence of long-term phonological memory traces. Copyright © 2018 Elsevier Inc. All rights reserved.

  5. Neural systems of second language reading are shaped by native language.

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    Tan, Li Hai; Spinks, John A; Feng, Ching-Mei; Siok, Wai Ting; Perfetti, Charles A; Xiong, Jinhu; Fox, Peter T; Gao, Jia-Hong

    2003-03-01

    Reading in a second language (L2) is a complex task that entails an interaction between L2 and the native language (L1). To study the underlying mechanisms, we used functional magnetic resonance imaging (fMRI) to visualize Chinese-English bilinguals' brain activity in phonological processing of logographic Chinese and alphabetic English, two written languages with a sharp contrast in phonology and orthography. In Experiment 1, we found that phonological processing of Chinese characters recruits a neural system involving left middle frontal and posterior parietal gyri, cortical regions that are known to contribute to spatial information representation, spatial working memory, and coordination of cognitive resources as a central executive system. We assume that the peak activation of this system is relevant to the unique feature of Chinese that a logographic character has a square configuration that maps onto a monosyllabic unit of speech. Equally important, when our bilingual subjects performed a phonological task on English words, this neural system was most active, whereas brain areas mediating English monolinguals' fine-grained phonemic analysis, as demonstrated by Experiment 2, were only weakly activated. This suggests that our bilingual subjects were applying their L1 system to L2 reading and that the lack of letter-to-sound conversion rules in Chinese led Chinese readers to being less capable of processing English by recourse to an analytic reading system on which English monolinguals rely. Our brain imaging findings lend strongest support to the idea that language experience tunes the cortex. Copyright 2003 Wiley-Liss, Inc.

  6. The shared neural basis of music and language.

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    Yu, Mengxia; Xu, Miao; Li, Xueting; Chen, Zhencai; Song, Yiying; Liu, Jia

    2017-08-15

    Human musical ability is proposed to play a key phylogenetical role in the evolution of language, and the similarity of hierarchical structure in music and language has led to considerable speculation about their shared mechanisms. While behavioral and electrophysioglocial studies have revealed associations between music and linguistic abilities, results from functional magnetic resonance imaging (fMRI) studies on their relations are contradictory, possibly because these studies usually treat music or language as single entities without breaking down to their components. Here, we examined the relations between different components of music (i.e., melodic and rhythmic analysis) and language (i.e., semantic and phonological processing) using both behavioral tests and resting-state fMRI. Behaviorally, we found that individuals with music training experiences were better at semantic processing, but not at phonological processing, than those without training. Further correlation analyses showed that semantic processing of language was related to melodic, but not rhythmic, analysis of music. Neurally, we found that performances in both semantic processing and melodic analysis were correlated with spontaneous brain activities in the bilateral precentral gyrus (PCG) and superior temporal plane at the regional level, and with the resting-state functional connectivity of the left PCG with the left supramarginal gyrus and left superior temporal gyrus at the network level. Together, our study revealed the shared spontaneous neural basis of music and language based on the behavioral link between melodic analysis and semantic processing, which possibly relied on a common mechanism of automatic auditory-motor integration. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

  7. A Cognitive Neural Architecture Able to Learn and Communicate through Natural Language.

    Directory of Open Access Journals (Sweden)

    Bruno Golosio

    Full Text Available Communicative interactions involve a kind of procedural knowledge that is used by the human brain for processing verbal and nonverbal inputs and for language production. Although considerable work has been done on modeling human language abilities, it has been difficult to bring them together to a comprehensive tabula rasa system compatible with current knowledge of how verbal information is processed in the brain. This work presents a cognitive system, entirely based on a large-scale neural architecture, which was developed to shed light on the procedural knowledge involved in language elaboration. The main component of this system is the central executive, which is a supervising system that coordinates the other components of the working memory. In our model, the central executive is a neural network that takes as input the neural activation states of the short-term memory and yields as output mental actions, which control the flow of information among the working memory components through neural gating mechanisms. The proposed system is capable of learning to communicate through natural language starting from tabula rasa, without any a priori knowledge of the structure of phrases, meaning of words, role of the different classes of words, only by interacting with a human through a text-based interface, using an open-ended incremental learning process. It is able to learn nouns, verbs, adjectives, pronouns and other word classes, and to use them in expressive language. The model was validated on a corpus of 1587 input sentences, based on literature on early language assessment, at the level of about 4-years old child, and produced 521 output sentences, expressing a broad range of language processing functionalities.

  8. Neural associative memories for the integration of language, vision and action in an autonomous agent.

    Science.gov (United States)

    Markert, H; Kaufmann, U; Kara Kayikci, Z; Palm, G

    2009-03-01

    Language understanding is a long-standing problem in computer science. However, the human brain is capable of processing complex languages with seemingly no difficulties. This paper shows a model for language understanding using biologically plausible neural networks composed of associative memories. The model is able to deal with ambiguities on the single word and grammatical level. The language system is embedded into a robot in order to demonstrate the correct semantical understanding of the input sentences by letting the robot perform corresponding actions. For that purpose, a simple neural action planning system has been combined with neural networks for visual object recognition and visual attention control mechanisms.

  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. Social Interaction Affects Neural Outcomes of Sign Language Learning As a Foreign Language in Adults.

    Science.gov (United States)

    Yusa, Noriaki; Kim, Jungho; Koizumi, Masatoshi; Sugiura, Motoaki; Kawashima, Ryuta

    2017-01-01

    Children naturally acquire a language in social contexts where they interact with their caregivers. Indeed, research shows that social interaction facilitates lexical and phonological development at the early stages of child language acquisition. It is not clear, however, whether the relationship between social interaction and learning applies to adult second language acquisition of syntactic rules. Does learning second language syntactic rules through social interactions with a native speaker or without such interactions impact behavior and the brain? The current study aims to answer this question. Adult Japanese participants learned a new foreign language, Japanese sign language (JSL), either through a native deaf signer or via DVDs. Neural correlates of acquiring new linguistic knowledge were investigated using functional magnetic resonance imaging (fMRI). The participants in each group were indistinguishable in terms of their behavioral data after the instruction. The fMRI data, however, revealed significant differences in the neural activities between two groups. Significant activations in the left inferior frontal gyrus (IFG) were found for the participants who learned JSL through interactions with the native signer. In contrast, no cortical activation change in the left IFG was found for the group who experienced the same visual input for the same duration via the DVD presentation. Given that the left IFG is involved in the syntactic processing of language, spoken or signed, learning through social interactions resulted in an fMRI signature typical of native speakers: activation of the left IFG. Thus, broadly speaking, availability of communicative interaction is necessary for second language acquisition and this results in observed changes in the brain.

  11. Sign Language Recognition System using Neural Network for Digital Hardware Implementation

    International Nuclear Information System (INIS)

    Vargas, Lorena P; Barba, Leiner; Torres, C O; Mattos, L

    2011-01-01

    This work presents an image pattern recognition system using neural network for the identification of sign language to deaf people. The system has several stored image that show the specific symbol in this kind of language, which is employed to teach a multilayer neural network using a back propagation algorithm. Initially, the images are processed to adapt them and to improve the performance of discriminating of the network, including in this process of filtering, reduction and elimination noise algorithms as well as edge detection. The system is evaluated using the signs without including movement in their representation.

  12. Neural Cognition and Affective Computing on Cyber Language.

    Science.gov (United States)

    Huang, Shuang; Zhou, Xuan; Xue, Ke; Wan, Xiqiong; Yang, Zhenyi; Xu, Duo; Ivanović, Mirjana; Yu, Xueer

    2015-01-01

    Characterized by its customary symbol system and simple and vivid expression patterns, cyber language acts as not only a tool for convenient communication but also a carrier of abundant emotions and causes high attention in public opinion analysis, internet marketing, service feedback monitoring, and social emergency management. Based on our multidisciplinary research, this paper presents a classification of the emotional symbols in cyber language, analyzes the cognitive characteristics of different symbols, and puts forward a mechanism model to show the dominant neural activities in that process. Through the comparative study of Chinese, English, and Spanish, which are used by the largest population in the world, this paper discusses the expressive patterns of emotions in international cyber languages and proposes an intelligent method for affective computing on cyber language in a unified PAD (Pleasure-Arousal-Dominance) emotional space.

  13. Neural Cognition and Affective Computing on Cyber Language

    Directory of Open Access Journals (Sweden)

    Shuang Huang

    2015-01-01

    Full Text Available Characterized by its customary symbol system and simple and vivid expression patterns, cyber language acts as not only a tool for convenient communication but also a carrier of abundant emotions and causes high attention in public opinion analysis, internet marketing, service feedback monitoring, and social emergency management. Based on our multidisciplinary research, this paper presents a classification of the emotional symbols in cyber language, analyzes the cognitive characteristics of different symbols, and puts forward a mechanism model to show the dominant neural activities in that process. Through the comparative study of Chinese, English, and Spanish, which are used by the largest population in the world, this paper discusses the expressive patterns of emotions in international cyber languages and proposes an intelligent method for affective computing on cyber language in a unified PAD (Pleasure-Arousal-Dominance emotional space.

  14. ALPHABET SIGN LANGUAGE RECOGNITION USING LEAP MOTION TECHNOLOGY AND RULE BASED BACKPROPAGATION-GENETIC ALGORITHM NEURAL NETWORK (RBBPGANN

    Directory of Open Access Journals (Sweden)

    Wijayanti Nurul Khotimah

    2017-01-01

    Full Text Available Sign Language recognition was used to help people with normal hearing communicate effectively with the deaf and hearing-impaired. Based on survey that conducted by Multi-Center Study in Southeast Asia, Indonesia was on the top four position in number of patients with hearing disability (4.6%. Therefore, the existence of Sign Language recognition is important. Some research has been conducted on this field. Many neural network types had been used for recognizing many kinds of sign languages. However, their performance are need to be improved. This work focuses on the ASL (Alphabet Sign Language in SIBI (Sign System of Indonesian Language which uses one hand and 26 gestures. Here, thirty four features were extracted by using Leap Motion. Further, a new method, Rule Based-Backpropagation Genetic Al-gorithm Neural Network (RB-BPGANN, was used to recognize these Sign Languages. This method is combination of Rule and Back Propagation Neural Network (BPGANN. Based on experiment this pro-posed application can recognize Sign Language up to 93.8% accuracy. It was very good to recognize large multiclass instance and can be solution of overfitting problem in Neural Network algorithm.

  15. Time Series Neural Network Model for Part-of-Speech Tagging Indonesian Language

    Science.gov (United States)

    Tanadi, Theo

    2018-03-01

    Part-of-speech tagging (POS tagging) is an important part in natural language processing. Many methods have been used to do this task, including neural network. This paper models a neural network that attempts to do POS tagging. A time series neural network is modelled to solve the problems that a basic neural network faces when attempting to do POS tagging. In order to enable the neural network to have text data input, the text data will get clustered first using Brown Clustering, resulting a binary dictionary that the neural network can use. To further the accuracy of the neural network, other features such as the POS tag, suffix, and affix of previous words would also be fed to the neural network.

  16. Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System.

    Science.gov (United States)

    Zamora-Martinez, Francisco; Castro-Bleda, Maria Jose

    2018-02-22

    Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on [Formula: see text]-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and [Formula: see text]-gram-based systems, showing that the integrated approach seems more promising for [Formula: see text]-gram-based systems, even with nonfull-quality NNLMs.

  17. Computational modeling of neural plasticity for self-organization of neural networks.

    Science.gov (United States)

    Chrol-Cannon, Joseph; Jin, Yaochu

    2014-11-01

    Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  18. Neural Differences in Bilingual Children's Arithmetic Processing Depending on Language of Instruction

    NARCIS (Netherlands)

    Mondt, K.; Struys, E.; Noort, M.W.M.L. van den; Balériaux, D.; Metens, T.; Paquier, P.; Craen, P. van de; Bosch, M.P.C.; Denolin, V.

    2011-01-01

    Many children in bilingual regions follow lessons in a language at school (school-language) that they hardly ever speak at home or in other informal settings. What are the neural effects of this phenomenon? This functional magnetic resonance imaging (fMRI) study investigates the effects of using

  19. Exploiting Hidden Layer Responses of Deep Neural Networks for Language Recognition

    Science.gov (United States)

    2016-09-08

    Target Languages Arabic (ara) Egyptian , Iraqi, Levantine, Maghrebi,Modern Standard Chinese (chi) Cantonese, Mandarin, Min, Wu English (eng) British...Frame-by-frame DNN classification x1 x2 x3 xT-­1xT Figure 1: Frame-by-frame DNN Language Identification Figure 1 shows the architecture of the DNN...compare direct DNN system with proposed DNN I-vector system, we trained a single neural network to classify all 20 languages. The architecture of this

  20. Habituation in non-neural organisms: evidence from slime moulds

    OpenAIRE

    Boisseau, Romain P.; Vogel, David; Dussutour, Audrey

    2016-01-01

    Learning, defined as a change in behaviour evoked by experience, has hitherto been investigated almost exclusively in multicellular neural organisms. Evidence for learning in non-neural multicellular organisms is scant, and only a few unequivocal reports of learning have been described in single-celled organisms. Here we demonstrate habituation, an unmistakable form of learning, in the non-neural organism Physarum polycephalum. In our experiment, using chemotaxis as the behavioural output and...

  1. Neurolinguistics Aspects of Second Language Acquisition

    Directory of Open Access Journals (Sweden)

    Laleh Fakhraee Faruji

    2011-12-01

    Full Text Available   Fundamental breakthroughs in the neurosciences, combined with technical innovations for measuring brain activity, are shedding new light on the neural basis of second language (L2
    processing, and on its relationship to native language processing (L1 (Perani & Abutalebi, 2005.  Over the past two decades, a large body of neuroimaging studies has been devoted to the study of the neural organization of language (De´monet, Thierry, & Cardebat, 2005; Indefrey & Levelt, 2004; Price, 2000 as cited in Abutalebi, 2008. The value that functional neuroimaging adds to language research is to improve the perspective on the distributed anatomy of language. Thus, it can be used with considerable precision to identify the neural networks underlying the different domains of language processing. In this paper some main issues related to neurolinguistics and second language acquisition with a focus on bilingualism will be discussed.

  2. Neural convergence for language comprehension and grammatical class production in highly proficient bilinguals is independent of age of acquisition.

    Science.gov (United States)

    Consonni, Monica; Cafiero, Riccardo; Marin, Dario; Tettamanti, Marco; Iadanza, Antonella; Fabbro, Franco; Perani, Daniela

    2013-05-01

    In bilinguals, native (L1) and second (L2) languages are processed by the same neural resources that can be modulated by age of second language acquisition (AOA), proficiency level, and daily language exposure and usage. AOA seems to particularly affect grammar processing, where a complete neural convergence has been shown only in bilinguals with parallel language acquisition from birth. Despite the fact that proficiency-related neuroanatomical differences have been well documented in language comprehension (LC) and production, few reports have addressed the influence of language exposure. A still unanswered question pertains to the role of AOA, when proficiency is comparably high across languages, with respect to its modulator effects both on LC and production. Here, we evaluated with fMRI during sentence comprehension and verb and noun production tasks, two groups of highly proficient bilinguals only differing in AOA. One group learned Italian and Friulian in parallel from birth, whereas the second group learned Italian between 3 and 6 years. All participants were highly exposed to both languages, but more to Italian than Friulian. The results indicate a complete overlap of neural activations for the comprehension of both languages, not only in bilinguals from birth, but also in late bilinguals. A slightly extra activation in the left thalamus for the less-exposed language confirms that exposure may affect language processing. Noteworthy, we report for the first time that, when proficiency and exposure are kept high, noun and verb production recruit the same neural networks for L1 and L2, independently of AOA. These results support the neural convergence hypothesis. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Mirror neurons and the social nature of language: the neural exploitation hypothesis.

    Science.gov (United States)

    Gallese, Vittorio

    2008-01-01

    This paper discusses the relevance of the discovery of mirror neurons in monkeys and of the mirror neuron system in humans to a neuroscientific account of primates' social cognition and its evolution. It is proposed that mirror neurons and the functional mechanism they underpin, embodied simulation, can ground within a unitary neurophysiological explanatory framework important aspects of human social cognition. In particular, the main focus is on language, here conceived according to a neurophenomenological perspective, grounding meaning on the social experience of action. A neurophysiological hypothesis--the "neural exploitation hypothesis"--is introduced to explain how key aspects of human social cognition are underpinned by brain mechanisms originally evolved for sensorimotor integration. It is proposed that these mechanisms were later on adapted as new neurofunctional architecture for thought and language, while retaining their original functions as well. By neural exploitation, social cognition and language can be linked to the experiential domain of action.

  4. Neural Correlates of High Performance in Foreign Language Vocabulary Learning

    Science.gov (United States)

    Macedonia, Manuela; Muller, Karsten; Friederici, Angela D.

    2010-01-01

    Learning vocabulary in a foreign language is a laborious task which people perform with varying levels of success. Here, we investigated the neural underpinning of high performance on this task. In a within-subjects paradigm, participants learned 92 vocabulary items under two multimodal conditions: one condition paired novel words with iconic…

  5. Language Identification in Short Utterances Using Long Short-Term Memory (LSTM) Recurrent Neural Networks.

    Science.gov (United States)

    Zazo, Ruben; Lozano-Diez, Alicia; Gonzalez-Dominguez, Javier; Toledano, Doroteo T; Gonzalez-Rodriguez, Joaquin

    2016-01-01

    Long Short Term Memory (LSTM) Recurrent Neural Networks (RNNs) have recently outperformed other state-of-the-art approaches, such as i-vector and Deep Neural Networks (DNNs), in automatic Language Identification (LID), particularly when dealing with very short utterances (∼3s). In this contribution we present an open-source, end-to-end, LSTM RNN system running on limited computational resources (a single GPU) that outperforms a reference i-vector system on a subset of the NIST Language Recognition Evaluation (8 target languages, 3s task) by up to a 26%. This result is in line with previously published research using proprietary LSTM implementations and huge computational resources, which made these former results hardly reproducible. Further, we extend those previous experiments modeling unseen languages (out of set, OOS, modeling), which is crucial in real applications. Results show that a LSTM RNN with OOS modeling is able to detect these languages and generalizes robustly to unseen OOS languages. Finally, we also analyze the effect of even more limited test data (from 2.25s to 0.1s) proving that with as little as 0.5s an accuracy of over 50% can be achieved.

  6. Commonalities and differences in the neural representations of English, Portuguese, and Mandarin sentences: When knowledge of the brain-language mappings for two languages is better than one.

    Science.gov (United States)

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

    2017-12-01

    This study extended cross-language semantic decoding (based on a concept's fMRI signature) to the decoding of sentences across three different languages (English, Portuguese and Mandarin). A classifier was trained on either the mapping between words and activation patterns in one language or the mappings in two languages (using an equivalent amount of training data), and then tested on its ability to decode the semantic content of a third language. The model trained on two languages was reliably more accurate than a classifier trained on one language for all three pairs of languages. This two-language advantage was selective to abstract concept domains such as social interactions and mental activity. Representational Similarity Analyses (RSA) of the inter-sentence neural similarities resulted in similar clustering of sentences in all the three languages, indicating a shared neural concept space among languages. These findings identify semantic domains that are common across these three languages versus those that are more language or culture-specific. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. 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…

  8. On the nature and evolution of the neural bases of human language

    Science.gov (United States)

    Lieberman, Philip

    2002-01-01

    The traditional theory equating the brain bases of language with Broca's and Wernicke's neocortical areas is wrong. Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, and comprehending the meaning of sentences. When we hear or read a word, neural structures involved in the perception or real-world associations of the word are activated as well as posterior cortical regions adjacent to Wernicke's area. Many areas of the neocortex and subcortical structures support the cortical-striatal-cortical circuits that confer complex syntactic ability, speech production, and a large vocabulary. However, many of these structures also form part of the neural circuits regulating other aspects of behavior. For example, the basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human linguistic ability and abstract reasoning. The cerebellum, traditionally associated with motor control, is active in motor learning. The basal ganglia are also key elements in reward-based learning. Data from studies of Broca's aphasia, Parkinson's disease, hypoxia, focal brain damage, and a genetically transmitted brain anomaly (the putative "language gene," family KE), and from comparative studies of the brains and behavior of other species, demonstrate that the basal ganglia sequence the discrete elements that constitute a complete motor act, syntactic process, or thought process. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. As Dobzansky put it, "Nothing in biology makes sense except in the light of evolution" (cited in Mayr, 1982). That applies with as much force to the human brain and the neural bases of language as it does to the human foot or jaw. The converse follows: the mark of evolution on

  9. 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.

  10. fMRI of Simultaneous Interpretation Reveals the Neural Basis of Extreme Language Control.

    Science.gov (United States)

    Hervais-Adelman, Alexis; Moser-Mercer, Barbara; Michel, Christoph M; Golestani, Narly

    2015-12-01

    We used functional magnetic resonance imaging (fMRI) to examine the neural basis of extreme multilingual language control in a group of 50 multilingual participants. Comparing brain responses arising during simultaneous interpretation (SI) with those arising during simultaneous repetition revealed activation of regions known to be involved in speech perception and production, alongside a network incorporating the caudate nucleus that is known to be implicated in domain-general cognitive control. The similarity between the networks underlying bilingual language control and general executive control supports the notion that the frequently reported bilingual advantage on executive tasks stems from the day-to-day demands of language control in the multilingual brain. We examined neural correlates of the management of simultaneity by correlating brain activity during interpretation with the duration of simultaneous speaking and hearing. This analysis showed significant modulation of the putamen by the duration of simultaneity. Our findings suggest that, during SI, the caudate nucleus is implicated in the overarching selection and control of the lexico-semantic system, while the putamen is implicated in ongoing control of language output. These findings provide the first clear dissociation of specific dorsal striatum structures in polyglot language control, roles that are consistent with previously described involvement of these regions in nonlinguistic executive control. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. Habituation in non-neural organisms: evidence from slime moulds.

    Science.gov (United States)

    Boisseau, Romain P; Vogel, David; Dussutour, Audrey

    2016-04-27

    Learning, defined as a change in behaviour evoked by experience, has hitherto been investigated almost exclusively in multicellular neural organisms. Evidence for learning in non-neural multicellular organisms is scant, and only a few unequivocal reports of learning have been described in single-celled organisms. Here we demonstrate habituation, an unmistakable form of learning, in the non-neural organism Physarum polycephalum In our experiment, using chemotaxis as the behavioural output and quinine or caffeine as the stimulus, we showed that P. polycephalum learnt to ignore quinine or caffeine when the stimuli were repeated, but responded again when the stimulus was withheld for a certain time. Our results meet the principle criteria that have been used to demonstrate habituation: responsiveness decline and spontaneous recovery. To distinguish habituation from sensory adaptation or motor fatigue, we also show stimulus specificity. Our results point to the diversity of organisms lacking neurons, which likely display a hitherto unrecognized capacity for learning, and suggest that slime moulds may be an ideal model system in which to investigate fundamental mechanisms underlying learning processes. Besides, documenting learning in non-neural organisms such as slime moulds is centrally important to a comprehensive, phylogenetic understanding of when and where in the tree of life the earliest manifestations of learning evolved. © 2016 The Author(s).

  12. Self-organized critical neural networks

    International Nuclear Information System (INIS)

    Bornholdt, Stefan; Roehl, Torsten

    2003-01-01

    A mechanism for self-organization of the degree of connectivity in model neural networks is studied. Network connectivity is regulated locally on the basis of an order parameter of the global dynamics, which is estimated from an observable at the single synapse level. This principle is studied in a two-dimensional neural network with randomly wired asymmetric weights. In this class of networks, network connectivity is closely related to a phase transition between ordered and disordered dynamics. A slow topology change is imposed on the network through a local rewiring rule motivated by activity-dependent synaptic development: Neighbor neurons whose activity is correlated, on average develop a new connection while uncorrelated neighbors tend to disconnect. As a result, robust self-organization of the network towards the order disorder transition occurs. Convergence is independent of initial conditions, robust against thermal noise, and does not require fine tuning of parameters

  13. Static sign language recognition using 1D descriptors and neural networks

    Science.gov (United States)

    Solís, José F.; Toxqui, Carina; Padilla, Alfonso; Santiago, César

    2012-10-01

    A frame work for static sign language recognition using descriptors which represents 2D images in 1D data and artificial neural networks is presented in this work. The 1D descriptors were computed by two methods, first one consists in a correlation rotational operator.1 and second is based on contour analysis of hand shape. One of the main problems in sign language recognition is segmentation; most of papers report a special color in gloves or background for hand shape analysis. In order to avoid the use of gloves or special clothing, a thermal imaging camera was used to capture images. Static signs were picked up from 1 to 9 digits of American Sign Language, a multilayer perceptron reached 100% recognition with cross-validation.

  14. Neural correlates of British sign language comprehension: spatial processing demands of topographic language.

    Science.gov (United States)

    MacSweeney, Mairéad; Woll, Bencie; Campbell, Ruth; Calvert, Gemma A; McGuire, Philip K; David, Anthony S; Simmons, Andrew; Brammer, Michael J

    2002-10-01

    In all signed languages used by deaf people, signs are executed in "sign space" in front of the body. Some signed sentences use this space to map detailed "real-world" spatial relationships directly. Such sentences can be considered to exploit sign space "topographically." Using functional magnetic resonance imaging, we explored the extent to which increasing the topographic processing demands of signed sentences was reflected in the differential recruitment of brain regions in deaf and hearing native signers of the British Sign Language. When BSL signers performed a sentence anomaly judgement task, the occipito-temporal junction was activated bilaterally to a greater extent for topographic than nontopographic processing. The differential role of movement in the processing of the two sentence types may account for this finding. In addition, enhanced activation was observed in the left inferior and superior parietal lobules during processing of topographic BSL sentences. We argue that the left parietal lobe is specifically involved in processing the precise configuration and location of hands in space to represent objects, agents, and actions. Importantly, no differences in these regions were observed when hearing people heard and saw English translations of these sentences. Despite the high degree of similarity in the neural systems underlying signed and spoken languages, exploring the linguistic features which are unique to each of these broadens our understanding of the systems involved in language comprehension.

  15. Self-Organizing Map Models of Language Acquisition

    Directory of Open Access Journals (Sweden)

    Ping eLi

    2013-11-01

    Full Text Available Connectionist models have had a profound impact on theories of language. While most early models were inspired by the classic PDP architecture, recent models of language have explored various other types of models, including self-organizing models for language acquisition. In this paper we aim at providing a review of the latter type of models, and highlight a number of simulation experiments that we have conducted based on these models. We show that self-organizing connectionist models can provide significant insights into long-standing debates in both monolingual and bilingual language development.

  16. From Imitation to Prediction, Data Compression vs Recurrent Neural Networks for Natural Language Processing

    Directory of Open Access Journals (Sweden)

    Juan Andres Laura

    2018-03-01

    Full Text Available In recent studies Recurrent Neural Networks were used for generative processes and their surprising performance can be explained by their ability to create good predictions. In addition, Data Compression is also based on prediction. What the problem comes down to is whether a data compressor could be used to perform as well as recurrent neural networks in the natural language processing tasks of sentiment analysis and automatic text generation. If this is possible, then the problem comes down to determining if a compression algorithm is even more intelligent than a neural network in such tasks. In our journey, a fundamental difference between a Data Compression Algorithm and Recurrent Neural Networks has been discovered.

  17. Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

    Science.gov (United States)

    Zhang, WenJun

    2007-07-01

    Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance

  18. Interactive natural language acquisition in a multi-modal recurrent neural architecture

    Science.gov (United States)

    Heinrich, Stefan; Wermter, Stefan

    2018-01-01

    For the complex human brain that enables us to communicate in natural language, we gathered good understandings of principles underlying language acquisition and processing, knowledge about sociocultural conditions, and insights into activity patterns in the brain. However, we were not yet able to understand the behavioural and mechanistic characteristics for natural language and how mechanisms in the brain allow to acquire and process language. In bridging the insights from behavioural psychology and neuroscience, the goal of this paper is to contribute a computational understanding of appropriate characteristics that favour language acquisition. Accordingly, we provide concepts and refinements in cognitive modelling regarding principles and mechanisms in the brain and propose a neurocognitively plausible model for embodied language acquisition from real-world interaction of a humanoid robot with its environment. In particular, the architecture consists of a continuous time recurrent neural network, where parts have different leakage characteristics and thus operate on multiple timescales for every modality and the association of the higher level nodes of all modalities into cell assemblies. The model is capable of learning language production grounded in both, temporal dynamic somatosensation and vision, and features hierarchical concept abstraction, concept decomposition, multi-modal integration, and self-organisation of latent representations.

  19. Organic and Non-Organic Language Disorders after Awake Brain Surgery

    Directory of Open Access Journals (Sweden)

    Elke De Witte

    2014-04-01

    Full Text Available INTRODUCTION: Awake surgery with Direct Electrical Stimulation (DES is considered the ‘gold standard’ to resect brain tumours in the language dominant hemisphere (De Witte & Mariën, 2013. Although transient language impairments are common in the immediate postoperative phase, permanent postoperative language deficits seem to be rare (Duffau, 2007. Milian et al. (2014 stated that most patients tolerate the awake procedure well and would undergo a similar procedure again. However, postoperative psychological symptoms including recurrent distressing dreams and persistent avoidance of stimuli have been recorded following awake surgery (Goebel, Nabavi, Schubert, & Mehdorn, 2010; Milian et al., 2014. To the best of our knowledge, psychogenic language disturbances have never been described after awake surgery. In general, only a handful of non-organic, psychogenic language disorders have been reported in the literature (De Letter et al., 2012. We report three patients with left brain tumours (see table 1 who presented linguistic symptoms after awake surgery that were incompatible with the lesion location, suggesting a psychogenic origin. METHODS: Neurocognitive (language, memory, executive functions investigations were carried out before, during and after awake surgery (6 weeks, 6 months postsurgery on the basis of standardised tests. Pre- and postoperative (fMRI images, DTI results and intraoperative DES findings were analysed. A selection of tasks was used to map language intraoperatively (De Witte et al., 2013. In the postoperative phase spontaneous speech and behavioural phenomena to errors were video-recorded. RESULTS: Preoperative language tests did not reveal any speech or language problems. Intraoperatively, eloquent sites were mapped and preserved enabling good language skills at the end of the awake procedure. However, assessments in the first weeks postsurgery disclosed language and behavioural symptoms that support the hypothesis of a

  20. Low-level neural auditory discrimination dysfunctions in specific language impairment—A review on mismatch negativity findings

    Directory of Open Access Journals (Sweden)

    Teija Kujala

    2017-12-01

    Full Text Available In specific language impairment (SLI, there is a delay in the child’s oral language skills when compared with nonverbal cognitive abilities. The problems typically relate to phonological and morphological processing and word learning. This article reviews studies which have used mismatch negativity (MMN in investigating low-level neural auditory dysfunctions in this disorder. With MMN, it is possible to tap the accuracy of neural sound discrimination and sensory memory functions. These studies have found smaller response amplitudes and longer latencies for speech and non-speech sound changes in children with SLI than in typically developing children, suggesting impaired and slow auditory discrimination in SLI. Furthermore, they suggest shortened sensory memory duration and vulnerability of the sensory memory to masking effects. Importantly, some studies reported associations between MMN parameters and language test measures. In addition, it was found that language intervention can influence the abnormal MMN in children with SLI, enhancing its amplitude. These results suggest that the MMN can shed light on the neural basis of various auditory and memory impairments in SLI, which are likely to influence speech perception. Keywords: Specific language impairment, Auditory processing, Mismatch negativity (MMN

  1. Cognitive processes and neural basis of language switching: proposal of a new model.

    Science.gov (United States)

    Moritz-Gasser, Sylvie; Duffau, Hugues

    2009-12-09

    Although studies on bilingualism are abundant, cognitive processes and neural foundations of language switching received less attention. The aim of our study is to provide new insights to this still open question: do dedicated region(s) for language switching exist or is this function underlain by a distributed circuit of interconnected brain areas, part of a more general cognitive system? On the basis of recent behavioral, neuroimaging, and brain stimulation studies, we propose an original 'hodological' model of language switching. This process might be subserved by a large-scale cortico-subcortical network, with an executive system (prefrontal cortex, anterior cingulum, caudate nucleus) controlling a more dedicated language subcircuit, which involves postero-temporal areas, supramarginal and angular gyri, Broca's area, and the superior longitudinal fasciculus.

  2. Review of Data Preprocessing Methods for Sign Language Recognition Systems based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Zorins Aleksejs

    2016-12-01

    Full Text Available The article presents an introductory analysis of relevant research topic for Latvian deaf society, which is the development of the Latvian Sign Language Recognition System. More specifically the data preprocessing methods are discussed in the paper and several approaches are shown with a focus on systems based on artificial neural networks, which are one of the most successful solutions for sign language recognition task.

  3. On Training Bi-directional Neural Network Language Model with Noise Contrastive Estimation

    OpenAIRE

    He, Tianxing; Zhang, Yu; Droppo, Jasha; Yu, Kai

    2016-01-01

    We propose to train bi-directional neural network language model(NNLM) with noise contrastive estimation(NCE). Experiments are conducted on a rescore task on the PTB data set. It is shown that NCE-trained bi-directional NNLM outperformed the one trained by conventional maximum likelihood training. But still(regretfully), it did not out-perform the baseline uni-directional NNLM.

  4. From phonemes to images : levels of representation in a recurrent neural model of visually-grounded language learning

    NARCIS (Netherlands)

    Gelderloos, L.J.; Chrupala, Grzegorz

    2016-01-01

    We present a model of visually-grounded language learning based on stacked gated recurrent neural networks which learns to predict visual features given an image description in the form of a sequence of phonemes. The learning task resembles that faced by human language learners who need to discover

  5. 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.

  6. Language Learning Enhanced by Massive Multiple Online Role-Playing Games (MMORPGs) and the Underlying Behavioral and Neural Mechanisms

    Science.gov (United States)

    Zhang, Yongjun; Song, Hongwen; Liu, Xiaoming; Tang, Dinghong; Chen, Yue-e; Zhang, Xiaochu

    2017-01-01

    Massive Multiple Online Role-Playing Games (MMORPGs) have increased in popularity among children, juveniles, and adults since MMORPGs’ appearance in this digital age. MMORPGs can be applied to enhancing language learning, which is drawing researchers’ attention from different fields and many studies have validated MMORPGs’ positive effect on language learning. However, there are few studies on the underlying behavioral or neural mechanism of such effect. This paper reviews the educational application of the MMORPGs based on relevant macroscopic and microscopic studies, showing that gamers’ overall language proficiency or some specific language skills can be enhanced by real-time online interaction with peers and game narratives or instructions embedded in the MMORPGs. Mechanisms underlying the educational assistant role of MMORPGs in second language learning are discussed from both behavioral and neural perspectives. We suggest that attentional bias makes gamers/learners allocate more cognitive resources toward task-related stimuli in a controlled or an automatic way. Moreover, with a moderating role played by activation of reward circuit, playing the MMORPGs may strengthen or increase functional connectivity from seed regions such as left anterior insular/frontal operculum (AI/FO) and visual word form area to other language-related brain areas. PMID:28303097

  7. Language Learning Enhanced by Massive Multiple Online Role-Playing Games (MMORPGs) and the Underlying Behavioral and Neural Mechanisms.

    Science.gov (United States)

    Zhang, Yongjun; Song, Hongwen; Liu, Xiaoming; Tang, Dinghong; Chen, Yue-E; Zhang, Xiaochu

    2017-01-01

    Massive Multiple Online Role-Playing Games (MMORPGs) have increased in popularity among children, juveniles, and adults since MMORPGs' appearance in this digital age. MMORPGs can be applied to enhancing language learning, which is drawing researchers' attention from different fields and many studies have validated MMORPGs' positive effect on language learning. However, there are few studies on the underlying behavioral or neural mechanism of such effect. This paper reviews the educational application of the MMORPGs based on relevant macroscopic and microscopic studies, showing that gamers' overall language proficiency or some specific language skills can be enhanced by real-time online interaction with peers and game narratives or instructions embedded in the MMORPGs. Mechanisms underlying the educational assistant role of MMORPGs in second language learning are discussed from both behavioral and neural perspectives. We suggest that attentional bias makes gamers/learners allocate more cognitive resources toward task-related stimuli in a controlled or an automatic way. Moreover, with a moderating role played by activation of reward circuit, playing the MMORPGs may strengthen or increase functional connectivity from seed regions such as left anterior insular/frontal operculum (AI/FO) and visual word form area to other language-related brain areas.

  8. Study of neural cells on organic semiconductor ultra thin films

    Energy Technology Data Exchange (ETDEWEB)

    Bystrenova, Eva; Tonazzini, Ilaria; Stoliar, Pablo; Greco, Pierpaolo; Lazar, Adina; Dutta, Soumya; Dionigi, Chiara; Cacace, Marcello; Biscarini, Fabio [ISMN-CNR, Bologna (Italy); Jelitai, Marta; Madarasz, Emilia [IEM- HAS, Budapest (Hungary); Huth, Martin; Nickel, Bert [LMU, Munich (Germany); Martini, Claudia [Dept. PNPB, Univ. of Pisa (Italy)

    2008-07-01

    Many technological advances are currently being developed for nano-fabrication, offering the ability to create and control patterns of soft materials. We report the deposition of cells on organic semiconductor ultra-thin films. This is a first step towards the development of active bio/non bio systems for electrical transduction. Thin films of pentacene, whose thickness was systematically varied, were grown by high vacuum sublimation. We report adhesion, growth, and differentiation of human astroglial cells and mouse neural stem cells on an organic semiconductor. Viability of astroglial cells in time was measured as a function of the roughness and the characteristic morphology of ultra thin organic film, as well as the features of the patterned molecules. Optical fluorescence microscope coupled to atomic force microscope was used to monitor the presence, density and shape of deposited cells. Neural stem cells remain viable, differentiate by retinoic acid and form dense neuronal networks. We have shown the possibility to integrate living neural cells on organic semiconductor thin films.

  9. Robots with language

    Directory of Open Access Journals (Sweden)

    Domenico Parisi

    2010-11-01

    Full Text Available Trying to understand human language by constructing robots that have language necessarily implies an embodied view of language, where the meaning of linguistic expressions is derived from the physical interactions of the organism with the environment. The paper describes a neural model of language according to which the robot’s behaviour is controlled by a neural network composed of two sub-networks, one dedicated to the non-linguistic interactions of the robot with the environment and the other one to processing linguistic input and producing linguistic output. We present the results of a number of simulations using the model and we suggest how the model can be used to account for various language-related phenomena such as disambiguation, the metaphorical use of words, the pervasive idiomaticity of multi-word expressions, and mental life as talking to oneself.. The model implies a view of the meaning of words and multi-word expressions as a temporal process that takes place in the entire brain and has no clearly defined boundaries. The model can also be extended to emotional words if we assume that an embodied view of language includes not only the interactions of the robot’s brain with the external environment but also the interactions of the brain with what is inside the body.

  10. Finger language recognition based on ensemble artificial neural network learning using armband EMG sensors.

    Science.gov (United States)

    Kim, Seongjung; Kim, Jongman; Ahn, Soonjae; Kim, Youngho

    2018-04-18

    Deaf people use sign or finger languages for communication, but these methods of communication are very specialized. For this reason, the deaf can suffer from social inequalities and financial losses due to their communication restrictions. In this study, we developed a finger language recognition algorithm based on an ensemble artificial neural network (E-ANN) using an armband system with 8-channel electromyography (EMG) sensors. The developed algorithm was composed of signal acquisition, filtering, segmentation, feature extraction and an E-ANN based classifier that was evaluated with the Korean finger language (14 consonants, 17 vowels and 7 numbers) in 17 subjects. E-ANN was categorized according to the number of classifiers (1 to 10) and size of training data (50 to 1500). The accuracy of the E-ANN-based classifier was obtained by 5-fold cross validation and compared with an artificial neural network (ANN)-based classifier. As the number of classifiers (1 to 8) and size of training data (50 to 300) increased, the average accuracy of the E-ANN-based classifier increased and the standard deviation decreased. The optimal E-ANN was composed with eight classifiers and 300 size of training data, and the accuracy of the E-ANN was significantly higher than that of the general ANN.

  11. Beyond the language given: the neural correlates of inferring speaker meaning.

    Science.gov (United States)

    Bašnáková, Jana; Weber, Kirsten; Petersson, Karl Magnus; van Berkum, Jos; Hagoort, Peter

    2014-10-01

    Even though language allows us to say exactly what we mean, we often use language to say things indirectly, in a way that depends on the specific communicative context. For example, we can use an apparently straightforward sentence like "It is hard to give a good presentation" to convey deeper meanings, like "Your talk was a mess!" One of the big puzzles in language science is how listeners work out what speakers really mean, which is a skill absolutely central to communication. However, most neuroimaging studies of language comprehension have focused on the arguably much simpler, context-independent process of understanding direct utterances. To examine the neural systems involved in getting at contextually constrained indirect meaning, we used functional magnetic resonance imaging as people listened to indirect replies in spoken dialog. Relative to direct control utterances, indirect replies engaged dorsomedial prefrontal cortex, right temporo-parietal junction and insula, as well as bilateral inferior frontal gyrus and right medial temporal gyrus. This suggests that listeners take the speaker's perspective on both cognitive (theory of mind) and affective (empathy-like) levels. In line with classic pragmatic theories, our results also indicate that currently popular "simulationist" accounts of language comprehension fail to explain how listeners understand the speaker's intended message. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  12. Musical aptitude and second language pronunciation skills in school-aged children: neural and behavioral evidence.

    Science.gov (United States)

    Milovanov, Riia; Huotilainen, Minna; Välimäki, Vesa; Esquef, Paulo A A; Tervaniemi, Mari

    2008-02-15

    The main focus of this study was to examine the relationship between musical aptitude and second language pronunciation skills. We investigated whether children with superior performance in foreign language production represent musical sound features more readily in the preattentive level of neural processing compared with children with less-advanced production skills. Sound processing accuracy was examined in elementary school children by means of event-related potential (ERP) recordings and behavioral measures. Children with good linguistic skills had better musical skills as measured by the Seashore musicality test than children with less accurate linguistic skills. The ERP data accompany the results of the behavioral tests: children with good linguistic skills showed more pronounced sound-change evoked activation with the music stimuli than children with less accurate linguistic skills. Taken together, the results imply that musical and linguistic skills could partly be based on shared neural mechanisms.

  13. A Neural Assembly-Based View on Word Production: The Bilingual Test Case

    Science.gov (United States)

    Strijkers, Kristof

    2016-01-01

    I will propose a tentative framework of how words in two languages could be organized in the cerebral cortex based on neural assembly theory, according to which neurons that fire synchronously are bound into large-scale distributed functional units (assemblies), which represent a mental event as a whole ("gestalt"). For language this…

  14. Brief Report: Anomalous Neural Deactivations and Functional Connectivity during Receptive Language in Autism Spectrum Disorder--A Functional MRI Study

    Science.gov (United States)

    Karten, Ariel; Hirsch, Joy

    2015-01-01

    Neural mechanisms that underlie language disability in autism spectrum disorder (ASD) have been associated with reduced excitatory processes observed as positive blood oxygen level dependent (BOLD) responses. However, negative BOLD responses (NBR) associated with language and inhibitory processes have been less studied in ASD. In this study,…

  15. Linguistic diversity and English language use in multicultural organizations

    DEFF Research Database (Denmark)

    Lauring, Jakob; Selmer, Jan

    2013-01-01

    Two great human resource management challenges face organizations in many parts of the world. The workforce is aging leaving fewer young people to take over. At the same time, globalization leads to a pressure for internationalization with great consequences for internal collaboration in many...... organizations. Accordingly, the link between employee age and language use is of increasing importance. In this study, we report on the findings of a survey using responses from 489 members of Danish multicultural organizations. We studied the effect of linguistic diversity on English language communication...... as well as the moderating effect of respondents’ age.Wefound linguistic diversity to have positive associations with the two English language communication variables. We also found age to moderate the relationship between linguistic diversity and perceived use of English language by management. Since...

  16. How age of bilingual exposure can change the neural systems for language in the developing brain: a functional near infrared spectroscopy investigation of syntactic processing in monolingual and bilingual children.

    Science.gov (United States)

    Jasinska, K K; Petitto, L A

    2013-10-01

    Is the developing bilingual brain fundamentally similar to the monolingual brain (e.g., neural resources supporting language and cognition)? Or, does early-life bilingual language experience change the brain? If so, how does age of first bilingual exposure impact neural activation for language? We compared how typically-developing bilingual and monolingual children (ages 7-10) and adults recruit brain areas during sentence processing using functional Near Infrared Spectroscopy (fNIRS) brain imaging. Bilingual participants included early-exposed (bilingual exposure from birth) and later-exposed individuals (bilingual exposure between ages 4-6). Both bilingual children and adults showed greater neural activation in left-hemisphere classic language areas, and additionally, right-hemisphere homologues (Right Superior Temporal Gyrus, Right Inferior Frontal Gyrus). However, important differences were observed between early-exposed and later-exposed bilinguals in their earliest-exposed language. Early bilingual exposure imparts fundamental changes to classic language areas instead of alterations to brain regions governing higher cognitive executive functions. However, age of first bilingual exposure does matter. Later-exposed bilinguals showed greater recruitment of the prefrontal cortex relative to early-exposed bilinguals and monolinguals. The findings provide fascinating insight into the neural resources that facilitate bilingual language use and are discussed in terms of how early-life language experiences can modify the neural systems underlying human language processing. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

  17. Germ layers, the neural crest and emergent organization in development and evolution.

    Science.gov (United States)

    Hall, Brian K

    2018-04-10

    Discovered in chick embryos by Wilhelm His in 1868 and named the neural crest by Arthur Milnes Marshall in 1879, the neural crest cells that arise from the neural folds have since been shown to differentiate into almost two dozen vertebrate cell types and to have played major roles in the evolution of such vertebrate features as bone, jaws, teeth, visceral (pharyngeal) arches, and sense organs. I discuss the discovery that ectodermal neural crest gave rise to mesenchyme and the controversy generated by that finding; the germ layer theory maintained that only mesoderm could give rise to mesenchyme. A second topic of discussion is germ layers (including the neural crest) as emergent levels of organization in animal development and evolution that facilitated major developmental and evolutionary change. The third topic is gene networks, gene co-option, and the evolution of gene-signaling pathways as key to developmental and evolutionary transitions associated with the origin and evolution of the neural crest and neural crest cells. © 2018 Wiley Periodicals, Inc.

  18. A review of organic and inorganic biomaterials for neural interfaces.

    Science.gov (United States)

    Fattahi, Pouria; Yang, Guang; Kim, Gloria; Abidian, Mohammad Reza

    2014-03-26

    Recent advances in nanotechnology have generated wide interest in applying nanomaterials for neural prostheses. An ideal neural interface should create seamless integration into the nervous system and performs reliably for long periods of time. As a result, many nanoscale materials not originally developed for neural interfaces become attractive candidates to detect neural signals and stimulate neurons. In this comprehensive review, an overview of state-of-the-art microelectrode technologies provided fi rst, with focus on the material properties of these microdevices. The advancements in electro active nanomaterials are then reviewed, including conducting polymers, carbon nanotubes, graphene, silicon nanowires, and hybrid organic-inorganic nanomaterials, for neural recording, stimulation, and growth. Finally, technical and scientific challenges are discussed regarding biocompatibility, mechanical mismatch, and electrical properties faced by these nanomaterials for the development of long-lasting functional neural interfaces.

  19. Neural correlates of language variability in preschool-aged boys with autism spectrum disorder.

    Science.gov (United States)

    Naigles, Letitia R; Johnson, Ryan; Mastergeorge, Ann; Ozonoff, Sally; Rogers, Sally J; Amaral, David G; Nordahl, Christine Wu

    2017-06-01

    Children with autism vary widely in their language abilities, yet the neural correlates of this language variability remain unclear, especially early in development. Diffusion tensor imaging (DTI) was used to examine diffusivity measures along the length of 18 major fiber tracts in 104 preschool-aged boys with autism spectrum disorder (ASD). The boys were assigned to subgroups according to their level of language development (Low: no/low language, Middle: small vocabulary, High: large vocabulary and grammar), based on their raw scores on the expressive language (EL) and receptive language (RL) sections of the Mullen Scales of Early Learning (MSEL). Results indicate that the subgroups differed in fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) along the inferior longitudinal fasciculus (ILF) in both hemispheres. Moreover, FA correlated significantly with Mullen EL and RL raw scores, but not ADOS severity score, along the left and right ILF. Subgroups also differed in MD (but not FA) along the left superior longitudinal fasiculus and left corticospinal tract, but these differences were not correlated with language scores. These findings suggest that white matter microstructure in the left and right ILF varies in relation to lexical development in young males with ASD. The findings also support the use of raw scores on language-relevant standardized tests for assessing early language-brain relationships. Autism Res 2017. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 1107-1119. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

  20. Innovative and Organized Approaches to Foreign Language Teaching

    Directory of Open Access Journals (Sweden)

    Max Florian Hertsch

    2013-03-01

    Full Text Available Innovation and organization in language education are more than just a teacher and students gathered in the same classroom at the same time, using the same materials and current motivation. The importance of innovations is highlighted by the European Label for innovative projects in language teaching and learning. For Turkey and its European Union membership ambitions, education is a prior section whose standard can be raised by innovations in foreign language education. Heyworth created a formula for innovations [C=(abc>x] which declares changes and its costs. The formula expresses that change for innovation equals several factors which must be more effective than the costs. In this article, Heyworth’s formula is transferred towards the language education system in Turkey. It will theoretically show advantages and changes and a way how Turkish organizations could change to provide more sustainable language education. Furthermore, the article will explain the already existing approaches and show their advantages and disadvantages. As a conclusion, a theoretical approach for innovations will be given and discussed.

  1. Self-Organizing Neural Circuits for Sensory-Guided Motor Control

    National Research Council Canada - National Science Library

    Grossberg, Stephen

    1999-01-01

    The reported projects developed mathematical models to explain how self-organizing neural circuits that operate under continuous or intermittent sensory guidance achieve flexible and accurate control of human movement...

  2. 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.

  3. Three-dimensional grammar in the brain: Dissociating the neural correlates of natural sign language and manually coded spoken language.

    Science.gov (United States)

    Jednoróg, Katarzyna; Bola, Łukasz; Mostowski, Piotr; Szwed, Marcin; Boguszewski, Paweł M; Marchewka, Artur; Rutkowski, Paweł

    2015-05-01

    In several countries natural sign languages were considered inadequate for education. Instead, new sign-supported systems were created, based on the belief that spoken/written language is grammatically superior. One such system called SJM (system językowo-migowy) preserves the grammatical and lexical structure of spoken Polish and since 1960s has been extensively employed in schools and on TV. Nevertheless, the Deaf community avoids using SJM for everyday communication, its preferred language being PJM (polski język migowy), a natural sign language, structurally and grammatically independent of spoken Polish and featuring classifier constructions (CCs). Here, for the first time, we compare, with fMRI method, the neural bases of natural vs. devised communication systems. Deaf signers were presented with three types of signed sentences (SJM and PJM with/without CCs). Consistent with previous findings, PJM with CCs compared to either SJM or PJM without CCs recruited the parietal lobes. The reverse comparison revealed activation in the anterior temporal lobes, suggesting increased semantic combinatory processes in lexical sign comprehension. Finally, PJM compared with SJM engaged left posterior superior temporal gyrus and anterior temporal lobe, areas crucial for sentence-level speech comprehension. We suggest that activity in these two areas reflects greater processing efficiency for naturally evolved sign language. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Cochlear Implantation (CI for prelingual deafness: the relevance of studies of brain organization and the role of first language acquisition in considering outcome success.

    Directory of Open Access Journals (Sweden)

    Ruth eCampbell

    2014-10-01

    Full Text Available Cochlear implantation (CI for profound congenital hearing impairment, while often successful in restoring hearing to the deaf child, does not always result in effective speech processing. Exposure to non-auditory signals during the pre-implantation period is widely held to be responsible for such failures. Here, we question the inference that such exposure irreparably distorts the function of auditory cortex, negatively impacting the efficacy of cochlear implantation. Animal studies suggest that in congenital early deafness there is a disconnection between (disordered activation in primary auditory cortex (A1 and activation in secondary auditory cortex (A2. In humans, one factor contributing to this functional decoupling is assumed to be abnormal activation of A1 by visual projections – including exposure to sign language. In this paper we show that that this abnormal activation of A1 does not routinely occur, while A2 functions effectively supramodally and multimodally to deliver spoken language irrespective of hearing status. What, then, is responsible for poor outcomes for some individuals with CI and for apparent abnormalities in cortical organization in these people? Since infancy is a critical period for the acquisition of language, deaf children born to hearing parents are at risk of developing inefficient neural structures to support skilled language processing. A sign language, acquired by a deaf child as a first language in a signing environment, is cortically organized like a heard spoken language in terms of specialization of the dominant perisylvian system. However, very few deaf children are exposed to sign language in early infancy. Moreover, no studies to date have examined sign language proficiency in relation to cortical organization in individuals with CI. Given the paucity of such relevant findings, we suggest that the best guarantee of good language outcome after CI is the establishment of a secure first language pre

  5. 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

  6. Language Learning Enhanced by Massive Multiple Online Role-Playing Games (MMORPGs) and the Underlying Behavioral and Neural Mechanisms

    OpenAIRE

    Zhang, Yongjun; Song, Hongwen; Liu, Xiaoming; Tang, Dinghong; Chen, Yue-e; Zhang, Xiaochu

    2017-01-01

    Massive Multiple Online Role-Playing Games (MMORPGs) have increased in popularity among children, juveniles, and adults since MMORPGs’ appearance in this digital age. MMORPGs can be applied to enhancing language learning, which is drawing researchers’ attention from different fields and many studies have validated MMORPGs’ positive effect on language learning. However, there are few studies on the underlying behavioral or neural mechanism of such effect. This paper reviews the educational app...

  7. Neural overlap in processing music and speech

    Science.gov (United States)

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L.

    2015-01-01

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. PMID:25646513

  8. Functional organization of the language network in three- and six-year-old children.

    Science.gov (United States)

    Vissiennon, Kodjo; Friederici, Angela D; Brauer, Jens; Wu, Chiao-Yi

    2017-04-01

    The organization of the language network undergoes continuous changes during development as children learn to understand sentences. In the present study, functional magnetic resonance imaging and behavioral measures were utilized to investigate functional activation and functional connectivity (FC) in three-year-old (3yo) and six-year-old (6yo) children during sentence comprehension. Transitive German sentences varying the word order (subject-initial and object-initial) with case marking were presented auditorily. We selected children who were capable of processing the subject-initial sentences above chance level accuracy from each age group to ensure that we were tapping real comprehension. Both age groups showed a main effect of word order in the left posterior superior temporal gyrus (pSTG), with greater activation for object-initial compared to subject-initial sentences. However, age differences were observed in the FC between left pSTG and the left inferior frontal gyrus (IFG). The 6yo group showed stronger FC between the left pSTG and Brodmann area (BA) 44 of the left IFG compared to the 3yo group. For the 3yo group, in turn, the FC between left pSTG and left BA 45 was stronger than with left BA 44. Our study demonstrates that while task-related activation was comparable, the small behavioral differences between age groups were reflected in the underlying functional organization revealing the ongoing development of the neural language network. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Tracking down abstract linguistic meaning: neural correlates of spatial frame of reference ambiguities in language.

    Directory of Open Access Journals (Sweden)

    Gabriele Janzen

    Full Text Available This functional magnetic resonance imaging (fMRI study investigates a crucial parameter in spatial description, namely variants in the frame of reference chosen. Two frames of reference are available in European languages for the description of small-scale assemblages, namely the intrinsic (or object-oriented frame and the relative (or egocentric frame. We showed participants a sentence such as "the ball is in front of the man", ambiguous between the two frames, and then a picture of a scene with a ball and a man--participants had to respond by indicating whether the picture did or did not match the sentence. There were two blocks, in which we induced each frame of reference by feedback. Thus for the crucial test items, participants saw exactly the same sentence and the same picture but now from one perspective, now the other. Using this method, we were able to precisely pinpoint the pattern of neural activation associated with each linguistic interpretation of the ambiguity, while holding the perceptual stimuli constant. Increased brain activity in bilateral parahippocampal gyrus was associated with the intrinsic frame of reference whereas increased activity in the right superior frontal gyrus and in the parietal lobe was observed for the relative frame of reference. The study is among the few to show a distinctive pattern of neural activation for an abstract yet specific semantic parameter in language. It shows with special clarity the nature of the neural substrate supporting each frame of spatial reference.

  10. Neural overlap in processing music and speech.

    Science.gov (United States)

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L

    2015-03-19

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  11. SORN: a self-organizing recurrent neural network

    Directory of Open Access Journals (Sweden)

    Andreea Lazar

    2009-10-01

    Full Text Available Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing circuits that learn appropriate representations for time-varying sensory stimuli. However, it has been difficult to mimic these abilities in artificial neural network models. Here we introduce SORN, a self-organizing recurrent network. It combines three distinct forms of local plasticity to learn spatio-temporal patterns in its input while maintaining its dynamics in a healthy regime suitable for learning. The SORN learns to encode information in the form of trajectories through its high-dimensional state space reminiscent of recent biological findings on cortical coding. All three forms of plasticity are shown to be essential for the network's success.

  12. Neural Basis of Action Understanding: Evidence from Sign Language Aphasia.

    Science.gov (United States)

    Rogalsky, Corianne; Raphel, Kristin; Tomkovicz, Vivian; O'Grady, Lucinda; Damasio, Hanna; Bellugi, Ursula; Hickok, Gregory

    2013-01-01

    The neural basis of action understanding is a hotly debated issue. The mirror neuron account holds that motor simulation in fronto-parietal circuits is critical to action understanding including speech comprehension, while others emphasize the ventral stream in the temporal lobe. Evidence from speech strongly supports the ventral stream account, but on the other hand, evidence from manual gesture comprehension (e.g., in limb apraxia) has led to contradictory findings. Here we present a lesion analysis of sign language comprehension. Sign language is an excellent model for studying mirror system function in that it bridges the gap between the visual-manual system in which mirror neurons are best characterized and language systems which have represented a theoretical target of mirror neuron research. Twenty-one life long deaf signers with focal cortical lesions performed two tasks: one involving the comprehension of individual signs and the other involving comprehension of signed sentences (commands). Participants' lesions, as indicated on MRI or CT scans, were mapped onto a template brain to explore the relationship between lesion location and sign comprehension measures. Single sign comprehension was not significantly affected by left hemisphere damage. Sentence sign comprehension impairments were associated with left temporal-parietal damage. We found that damage to mirror system related regions in the left frontal lobe were not associated with deficits on either of these comprehension tasks. We conclude that the mirror system is not critically involved in action understanding.

  13. Social in, social out: How the brain responds to social language with more social language.

    Science.gov (United States)

    O'Donnell, Matthew Brook; Falk, Emily B; Lieberman, Matthew D

    Social connection is a fundamental human need. As such, people's brains are sensitized to social cues, such as those carried by language, and to promoting social communication. The neural mechanisms of certain key building blocks in this process, such as receptivity to and reproduction of social language, however, are not known. We combined quantitative linguistic analysis and neuroimaging to connect neural activity in brain regions used to simulate the mental states of others with exposure to, and re-transmission of, social language. Our results link findings on successful idea transmission from communication science, sociolinguistics and cognitive neuroscience to prospectively predict the degree of social language that participants utilize when re-transmitting ideas as a function of 1) initial language inputs and 2) neural activity during idea exposure.

  14. 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.

  15. Mexican sign language recognition using normalized moments and artificial neural networks

    Science.gov (United States)

    Solís-V., J.-Francisco; Toxqui-Quitl, Carina; Martínez-Martínez, David; H.-G., Margarita

    2014-09-01

    This work presents a framework designed for the Mexican Sign Language (MSL) recognition. A data set was recorded with 24 static signs from the MSL using 5 different versions, this MSL dataset was captured using a digital camera in incoherent light conditions. Digital Image Processing was used to segment hand gestures, a uniform background was selected to avoid using gloved hands or some special markers. Feature extraction was performed by calculating normalized geometric moments of gray scaled signs, then an Artificial Neural Network performs the recognition using a 10-fold cross validation tested in weka, the best result achieved 95.83% of recognition rate.

  16. 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.

  17. Lexical Organization in Second Language Acquisition: Does the Critical Period Matter?

    Science.gov (United States)

    Cardimona, Kimberly; Smith, Pamela; Roberts, Lauren Sones

    2016-01-01

    This study examined lexical organization in English language learners (ELLs) who acquired their second language (L2) either during or after the period of maximal sensitivity related to the critical period hypothesis. Twenty-three native-Spanish-speaking ELLs completed psycholinguistic tasks to examine age effects in bilingual lexical organization.…

  18. Language and Cognition Interaction Neural Mechanisms

    Directory of Open Access Journals (Sweden)

    Leonid Perlovsky

    2011-01-01

    Full Text Available How language and cognition interact in thinking? Is language just used for communication of completed thoughts, or is it fundamental for thinking? Existing approaches have not led to a computational theory. We develop a hypothesis that language and cognition are two separate but closely interacting mechanisms. Language accumulates cultural wisdom; cognition develops mental representations modeling surrounding world and adapts cultural knowledge to concrete circumstances of life. Language is acquired from surrounding language “ready-made” and therefore can be acquired early in life. This early acquisition of language in childhood encompasses the entire hierarchy from sounds to words, to phrases, and to highest concepts existing in culture. Cognition is developed from experience. Yet cognition cannot be acquired from experience alone; language is a necessary intermediary, a “teacher.” A mathematical model is developed; it overcomes previous difficulties and leads to a computational theory. This model is consistent with Arbib's “language prewired brain” built on top of mirror neuron system. It models recent neuroimaging data about cognition, remaining unnoticed by other theories. A number of properties of language and cognition are explained, which previously seemed mysterious, including influence of language grammar on cultural evolution, which may explain specifics of English and Arabic cultures.

  19. Language and cognition interaction neural mechanisms.

    Science.gov (United States)

    Perlovsky, Leonid

    2011-01-01

    How language and cognition interact in thinking? Is language just used for communication of completed thoughts, or is it fundamental for thinking? Existing approaches have not led to a computational theory. We develop a hypothesis that language and cognition are two separate but closely interacting mechanisms. Language accumulates cultural wisdom; cognition develops mental representations modeling surrounding world and adapts cultural knowledge to concrete circumstances of life. Language is acquired from surrounding language "ready-made" and therefore can be acquired early in life. This early acquisition of language in childhood encompasses the entire hierarchy from sounds to words, to phrases, and to highest concepts existing in culture. Cognition is developed from experience. Yet cognition cannot be acquired from experience alone; language is a necessary intermediary, a "teacher." A mathematical model is developed; it overcomes previous difficulties and leads to a computational theory. This model is consistent with Arbib's "language prewired brain" built on top of mirror neuron system. It models recent neuroimaging data about cognition, remaining unnoticed by other theories. A number of properties of language and cognition are explained, which previously seemed mysterious, including influence of language grammar on cultural evolution, which may explain specifics of English and Arabic cultures.

  20. Language and Cognition Interaction Neural Mechanisms

    Science.gov (United States)

    Perlovsky, Leonid

    2011-01-01

    How language and cognition interact in thinking? Is language just used for communication of completed thoughts, or is it fundamental for thinking? Existing approaches have not led to a computational theory. We develop a hypothesis that language and cognition are two separate but closely interacting mechanisms. Language accumulates cultural wisdom; cognition develops mental representations modeling surrounding world and adapts cultural knowledge to concrete circumstances of life. Language is acquired from surrounding language “ready-made” and therefore can be acquired early in life. This early acquisition of language in childhood encompasses the entire hierarchy from sounds to words, to phrases, and to highest concepts existing in culture. Cognition is developed from experience. Yet cognition cannot be acquired from experience alone; language is a necessary intermediary, a “teacher.” A mathematical model is developed; it overcomes previous difficulties and leads to a computational theory. This model is consistent with Arbib's “language prewired brain” built on top of mirror neuron system. It models recent neuroimaging data about cognition, remaining unnoticed by other theories. A number of properties of language and cognition are explained, which previously seemed mysterious, including influence of language grammar on cultural evolution, which may explain specifics of English and Arabic cultures. PMID:21876687

  1. Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

    Science.gov (United States)

    Zhang, Xingyu; Kim, Joyce; Patzer, Rachel E; Pitts, Stephen R; Patzer, Aaron; Schrager, Justin D

    2017-10-26

    To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural language processing elements. Using data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), a cross-sectional probability sample of United States EDs from 2012 and 2013 survey years, we developed several predictive models with the outcome being admission to the hospital or transfer vs. discharge home. We included patient characteristics immediately available after the patient has presented to the ED and undergone a triage process. We used this information to construct logistic regression (LR) and multilayer neural network models (MLNN) which included natural language processing (NLP) and principal component analysis from the patient's reason for visit. Ten-fold cross validation was used to test the predictive capacity of each model and receiver operating curves (AUC) were then calculated for each model. Of the 47,200 ED visits from 642 hospitals, 6,335 (13.42%) resulted in hospital admission (or transfer). A total of 48 principal components were extracted by NLP from the reason for visit fields, which explained 75% of the overall variance for hospitalization. In the model including only structured variables, the AUC was 0.824 (95% CI 0.818-0.830) for logistic regression and 0.823 (95% CI 0.817-0.829) for MLNN. Models including only free-text information generated AUC of 0.742 (95% CI 0.731- 0.753) for logistic regression and 0.753 (95% CI 0.742-0.764) for MLNN. When both structured variables and free text variables were included, the AUC reached 0.846 (95% CI 0.839-0.853) for logistic regression and 0.844 (95% CI 0.836-0.852) for MLNN. The predictive accuracy of hospital admission or transfer for patients who presented to ED triage overall was good, and was improved with the inclusion of free text data from a patient

  2. Unique Neural Characteristics of Atypical Lateralization of Language in Healthy Individuals

    Directory of Open Access Journals (Sweden)

    Szymon P. Biduła

    2017-09-01

    Full Text Available Using functional magnetic resonance imaging (fMRI in 63 healthy participants, including left-handed and ambidextrous individuals, we tested how atypical lateralization of language—i. e., bilateral or right hemispheric language representation—differs from the typical left-hemisphere dominance. Although regardless of their handedness, all 11 participants from the atypical group engaged classical language centers, i.e., Broca's and Wernicke's areas, the right-hemisphere components of the default mode network (DMN, including the angular gyrus and middle temporal gyrus, were also critically involved during the verbal fluency task. Importantly, activity in these regions could not be explained in terms of mirroring the typical language pattern because left-hemisphere dominant individuals did not exhibit similar significant signal modulations. Moreover, when spatial extent of language-related activity across whole brain was considered, the bilateral language organization entailed more diffuse functional processing. Finally, we detected significant differences between the typical and atypical group in the resting-state connectivity at the global and local level. These findings suggest that the atypical lateralization of language has unique features, and is not a simple mirror image of the typical left hemispheric language representation.

  3. Music and language: relations and disconnections.

    Science.gov (United States)

    Kraus, Nina; Slater, Jessica

    2015-01-01

    Music and language provide an important context in which to understand the human auditory system. While they perform distinct and complementary communicative functions, music and language are both rooted in the human desire to connect with others. Since sensory function is ultimately shaped by what is biologically important to the organism, the human urge to communicate has been a powerful driving force in both the evolution of auditory function and the ways in which it can be changed by experience within an individual lifetime. This chapter emphasizes the highly interactive nature of the auditory system as well as the depth of its integration with other sensory and cognitive systems. From the origins of music and language to the effects of auditory expertise on the neural encoding of sound, we consider key themes in auditory processing, learning, and plasticity. We emphasize the unique role of the auditory system as the temporal processing "expert" in the brain, and explore relationships between communication and cognition. We demonstrate how experience with music and language can have a significant impact on underlying neural function, and that auditory expertise strengthens some of the very same aspects of sound encoding that are deficient in impaired populations. © 2015 Elsevier B.V. All rights reserved.

  4. Language and Cognition Interaction Neural Mechanisms

    OpenAIRE

    Perlovsky, Leonid

    2011-01-01

    How language and cognition interact in thinking? Is language just used for communication of completed thoughts, or is it fundamental for thinking? Existing approaches have not led to a computational theory. We develop a hypothesis that language and cognition are two separate but closely interacting mechanisms. Language accumulates cultural wisdom; cognition develops mental representations modeling surrounding world and adapts cultural knowledge to concrete circumstances of life. Language is a...

  5. Language-invariant verb processing regions in Spanish-English bilinguals.

    Science.gov (United States)

    Willms, Joanna L; Shapiro, Kevin A; Peelen, Marius V; Pajtas, Petra E; Costa, Albert; Moo, Lauren R; Caramazza, Alfonso

    2011-07-01

    Nouns and verbs are fundamental grammatical building blocks of all languages. Studies of brain-damaged patients and healthy individuals have demonstrated that verb processing can be dissociated from noun processing at a neuroanatomical level. In cases where bilingual patients have a noun or verb deficit, the deficit has been observed in both languages. This suggests that the noun-verb distinction may be based on neural components that are common across languages. Here we investigated the cortical organization of grammatical categories in healthy, early Spanish-English bilinguals using functional magnetic resonance imaging (fMRI) in a morphophonological alternation task. Four regions showed greater activity for verbs than for nouns in both languages: left posterior middle temporal gyrus (LMTG), left middle frontal gyrus (LMFG), pre-supplementary motor area (pre-SMA), and right middle occipital gyrus (RMOG); no regions showed greater activation for nouns. Multi-voxel pattern analysis within verb-specific regions showed indistinguishable activity patterns for English and Spanish, indicating language-invariant bilingual processing. In LMTG and LMFG, patterns were more similar within than across grammatical category, both within and across languages, indicating language-invariant grammatical class information. These results suggest that the neural substrates underlying verb-specific processing are largely independent of language in bilinguals, both at the macroscopic neuroanatomical level and at the level of voxel activity patterns. Copyright © 2011 Elsevier Inc. All rights reserved.

  6. Application of self-organizing competition artificial neural network to logging data explanation of sandstone-hosted uranium deposits

    International Nuclear Information System (INIS)

    Xu Jianguo; Xu Xianli; Wang Weiguo

    2008-01-01

    The article describes the model construction of self-organizing competition artificial neural network, its principle and automatic recognition process of borehole lithology in detail, and then proves the efficiency of the neural network model for automatically recognizing the borehole lithology with some cases. The self-organizing competition artificial neural network has the ability of self- organization, self-adjustment and high permitting errors. Compared with the BP algorithm, it takes less calculation quantity and more rapidly converges. Furthermore, it can automatically confirm the category without the known sample information. Trial results based on contrasting the identification results of the borehole lithology with geological documentations, indicate that self-organizing artificial neural network can be well applied to automatically performing the category of borehole lithology, during the logging data explanation of sandstone-hosted uranium deposits. (authors)

  7. Organization of Anti-Phase Synchronization Pattern in Neural Networks: What are the Key Factors?

    Science.gov (United States)

    Li, Dong; Zhou, Changsong

    2011-01-01

    Anti-phase oscillation has been widely observed in cortical neural network. Elucidating the mechanism underlying the organization of anti-phase pattern is of significance for better understanding more complicated pattern formations in brain networks. In dynamical systems theory, the organization of anti-phase oscillation pattern has usually been considered to relate to time delay in coupling. This is consistent to conduction delays in real neural networks in the brain due to finite propagation velocity of action potentials. However, other structural factors in cortical neural network, such as modular organization (connection density) and the coupling types (excitatory or inhibitory), could also play an important role. In this work, we investigate the anti-phase oscillation pattern organized on a two-module network of either neuronal cell model or neural mass model, and analyze the impact of the conduction delay times, the connection densities, and coupling types. Our results show that delay times and coupling types can play key roles in this organization. The connection densities may have an influence on the stability if an anti-phase pattern exists due to the other factors. Furthermore, we show that anti-phase synchronization of slow oscillations can be achieved with small delay times if there is interaction between slow and fast oscillations. These results are significant for further understanding more realistic spatiotemporal dynamics of cortico-cortical communications. PMID:22232576

  8. The N400 effect during speaker-switch – Towards a conversational approach of measuring neural correlates of language

    Directory of Open Access Journals (Sweden)

    Tatiana Goregliad Fjaellingsdal

    2016-11-01

    Full Text Available Language occurs naturally in conversations. However, the study of the neural underpinnings of language has mainly taken place in single individuals using controlled language material. The interactive elements of a conversation (e.g., turn-taking are often not part of neurolinguistic setups. The prime reason is the difficulty to combine open unrestricted conversations with the requirements of neuroimaging. It is necessary to find a trade-off between the naturalness of a conversation and the restrictions imposed by neuroscientific methods to allow for ecologically more valid studies.Here we make an attempt to study the effects of a conversational element, namely turn-taking, on linguistic neural correlates, specifically the N400 effect. We focus on the physiological aspect of turn-taking, the speaker-switch, and its effect on the detectability of the N400 effect. The N400 event-related potential reflects expectation violations in a semantic context; the N400 effect describes the difference of the N400 amplitude between semantically expected and unexpected items.Sentences with semantically congruent and incongruent final words were presented in two turn-taking modes: (1 reading aloud first part of the sentence and listening to speaker-switch for the final word, and (2 listening to first part of the sentence and speaker-switch for the final word.A significant N400 effect was found for both turn-taking modes, which was not influenced by the mode itself. However, the mode significantly affected the P200, which was increased for the reading aloud mode compared to the listening mode.Our results show that an N400 effect can be detected during a speaker-switch. Speech articulation (reading aloud before the analyzed sentence fragment did also not impede the N400 effect detection for the final word. The speaker-switch, however, seems to influence earlier components of the electroencephalogram, related to processing of salient stimuli. We conclude that the N

  9. Neural correlates of foreign-language learning in childhood: a 3-year longitudinal ERP study.

    Science.gov (United States)

    Ojima, Shiro; Nakamura, Naoko; Matsuba-Kurita, Hiroko; Hoshino, Takahiro; Hagiwara, Hiroko

    2011-01-01

    A foreign language (a language not spoken in one's community) is difficult to master completely. Early introduction of foreign-language (FL) education during childhood is becoming a standard in many countries. However, the neural process of child FL learning still remains largely unknown. We longitudinally followed 322 school-age children with diverse FL proficiency for three consecutive years, and acquired children's ERP responses to FL words that were semantically congruous or incongruous with the preceding picture context. As FL proficiency increased, various ERP components previously reported in mother-tongue (L1) acquisition (such as a broad negativity, an N400, and a late positive component) appeared sequentially, critically in an identical order to L1 acquisition. This finding was supported not only by cross-sectional analyses of children at different proficiency levels but also by longitudinal analyses of the same children over time. Our data are consistent with the hypothesis that FL learning in childhood reproduces identical developmental stages in an identical order to L1 acquisition, suggesting that the nature of the child's brain itself may determine the normal course of FL learning. Future research should test the generalizability of the results in other aspects of language such as syntax.

  10. Artificial neural network study on organ-targeting peptides

    Science.gov (United States)

    Jung, Eunkyoung; Kim, Junhyoung; Choi, Seung-Hoon; Kim, Minkyoung; Rhee, Hokyoung; Shin, Jae-Min; Choi, Kihang; Kang, Sang-Kee; Lee, Nam Kyung; Choi, Yun-Jaie; Jung, Dong Hyun

    2010-01-01

    We report a new approach to studying organ targeting of peptides on the basis of peptide sequence information. The positive control data sets consist of organ-targeting peptide sequences identified by the peroral phage-display technique for four organs, and the negative control data are prepared from random sequences. The capacity of our models to make appropriate predictions is validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). VHSE descriptor produces statistically significant training models and the models with simple neural network architectures show slightly greater predictive power than those with complex ones. The training and test set statistics indicate that our models could discriminate between organ-targeting and random sequences. We anticipate that our models will be applicable to the selection of organ-targeting peptides for generating peptide drugs or peptidomimetics.

  11. Appraisal Psychology, Neurobiology, and Language.

    Science.gov (United States)

    Schumann, John H.

    2001-01-01

    Proposes that the confluence of stimulus appraisal and social cognition that is effected by the neural system in the brain has important implications for language and learning theories. Describes the anatomy and functions of this neural system and discusses how it may operate in motivation for second language acquisition and how in conjunction…

  12. Identification-based chaos control via backstepping design using self-organizing fuzzy neural networks

    International Nuclear Information System (INIS)

    Peng Yafu; Hsu, C.-F.

    2009-01-01

    This paper proposes an identification-based adaptive backstepping control (IABC) for the chaotic systems. The IABC system is comprised of a neural backstepping controller and a robust compensation controller. The neural backstepping controller containing a self-organizing fuzzy neural network (SOFNN) identifier is the principal controller, and the robust compensation controller is designed to dispel the effect of minimum approximation error introduced by the SOFNN identifier. The SOFNN identifier is used to online estimate the chaotic dynamic function with structure and parameter learning phases of fuzzy neural network. The structure learning phase consists of the growing and pruning of fuzzy rules; thus the SOFNN identifier can avoid the time-consuming trial-and-error tuning procedure for determining the neural structure of fuzzy neural network. The parameter learning phase adjusts the interconnection weights of neural network to achieve favorable approximation performance. Finally, simulation results verify that the proposed IABC can achieve favorable tracking performance.

  13. The neural correlates of highly iconic structures and topographic discourse in French Sign Language as observed in six hearing native signers.

    Science.gov (United States)

    Courtin, C; Hervé, P-Y; Petit, L; Zago, L; Vigneau, M; Beaucousin, V; Jobard, G; Mazoyer, B; Mellet, E; Tzourio-Mazoyer, N

    2010-09-01

    "Highly iconic" structures in Sign Language enable a narrator to act, switch characters, describe objects, or report actions in four-dimensions. This group of linguistic structures has no real spoken-language equivalent. Topographical descriptions are also achieved in a sign-language specific manner via the use of signing-space and spatial-classifier signs. We used functional magnetic resonance imaging (fMRI) to compare the neural correlates of topographic discourse and highly iconic structures in French Sign Language (LSF) in six hearing native signers, children of deaf adults (CODAs), and six LSF-naïve monolinguals. LSF materials consisted of videos of a lecture excerpt signed without spatially organized discourse or highly iconic structures (Lect LSF), a tale signed using highly iconic structures (Tale LSF), and a topographical description using a diagrammatic format and spatial-classifier signs (Topo LSF). We also presented texts in spoken French (Lect French, Tale French, Topo French) to all participants. With both languages, the Topo texts activated several different regions that are involved in mental navigation and spatial working memory. No specific correlate of LSF spatial discourse was evidenced. The same regions were more activated during Tale LSF than Lect LSF in CODAs, but not in monolinguals, in line with the presence of signing-space structure in both conditions. Motion processing areas and parts of the fusiform gyrus and precuneus were more active during Tale LSF in CODAs; no such effect was observed with French or in LSF-naïve monolinguals. These effects may be associated with perspective-taking and acting during personal transfers. 2010 Elsevier Inc. All rights reserved.

  14. Time, Language and Action - A Unified Long-Term Memory Model for Sensory-Motor Chains and Word Schemata

    OpenAIRE

    Chersi, Fabian; Ferro, Marcello; Pezzulo, Giovanni; Pirrelli, Vito

    2011-01-01

    Action and language are known to be organized as closely-related brain subsystems. An Italian CNR project implemented a computational neural model where the ability to form chains of goal-directed actions and chains of linguistic units relies on a unified memory architecture obeying the same organizing principles.

  15. RM-SORN: a reward-modulated self-organizing recurrent neural network.

    Science.gov (United States)

    Aswolinskiy, Witali; Pipa, Gordon

    2015-01-01

    Neural plasticity plays an important role in learning and memory. Reward-modulation of plasticity offers an explanation for the ability of the brain to adapt its neural activity to achieve a rewarded goal. Here, we define a neural network model that learns through the interaction of Intrinsic Plasticity (IP) and reward-modulated Spike-Timing-Dependent Plasticity (STDP). IP enables the network to explore possible output sequences and STDP, modulated by reward, reinforces the creation of the rewarded output sequences. The model is tested on tasks for prediction, recall, non-linear computation, pattern recognition, and sequence generation. It achieves performance comparable to networks trained with supervised learning, while using simple, biologically motivated plasticity rules, and rewarding strategies. The results confirm the importance of investigating the interaction of several plasticity rules in the context of reward-modulated learning and whether reward-modulated self-organization can explain the amazing capabilities of the brain.

  16. ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network.

    Science.gov (United States)

    Cao, Renzhi; Freitas, Colton; Chan, Leong; Sun, Miao; Jiang, Haiqing; Chen, Zhangxin

    2017-10-17

    With the development of next generation sequencing techniques, it is fast and cheap to determine protein sequences but relatively slow and expensive to extract useful information from protein sequences because of limitations of traditional biological experimental techniques. Protein function prediction has been a long standing challenge to fill the gap between the huge amount of protein sequences and the known function. In this paper, we propose a novel method to convert the protein function problem into a language translation problem by the new proposed protein sequence language "ProLan" to the protein function language "GOLan", and build a neural machine translation model based on recurrent neural networks to translate "ProLan" language to "GOLan" language. We blindly tested our method by attending the latest third Critical Assessment of Function Annotation (CAFA 3) in 2016, and also evaluate the performance of our methods on selected proteins whose function was released after CAFA competition. The good performance on the training and testing datasets demonstrates that our new proposed method is a promising direction for protein function prediction. In summary, we first time propose a method which converts the protein function prediction problem to a language translation problem and applies a neural machine translation model for protein function prediction.

  17. ORGANIC ELECTRODE COATINGS FOR NEXT-GENERATION NEURAL INTERFACES

    Directory of Open Access Journals (Sweden)

    Ulises A Aregueta-Robles

    2014-05-01

    Full Text Available Traditional neuronal interfaces utilize metallic electrodes which in recent years have reached a plateau in terms of the ability to provide safe stimulation at high resolution or rather with high densities of microelectrodes with improved spatial selectivity. To achieve higher resolution it has become clear that reducing the size of electrodes is required to enable higher electrode counts from the implant device. The limitations of interfacing electrodes including low charge injection limits, mechanical mismatch and foreign body response can be addressed through the use of organic electrode coatings which typically provide a softer, more roughened surface to enable both improved charge transfer and lower mechanical mismatch with neural tissue. Coating electrodes with conductive polymers or carbon nanotubes offers a substantial increase in charge transfer area compared to conventional platinum electrodes. These organic conductors provide safe electrical stimulation of tissue while avoiding undesirable chemical reactions and cell damage. However, the mechanical properties of conductive polymers are not ideal, as they are quite brittle. Hydrogel polymers present a versatile coating option for electrodes as they can be chemically modified to provide a soft and conductive scaffold. However, the in vivo chronic inflammatory response of these conductive hydrogels remains unknown. A more recent approach proposes tissue engineering the electrode interface through the use of encapsulated neurons within hydrogel coatings. This approach may provide a method for activating tissue at the cellular scale, however several technological challenges must be addressed to demonstrate feasibility of this innovative idea. The review focuses on the various organic coatings which have been investigated to improve neural interface electrodes.

  18. 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.

  19. Morphological self-organizing feature map neural network with applications to automatic target recognition

    Science.gov (United States)

    Zhang, Shijun; Jing, Zhongliang; Li, Jianxun

    2005-01-01

    The rotation invariant feature of the target is obtained using the multi-direction feature extraction property of the steerable filter. Combining the morphological operation top-hat transform with the self-organizing feature map neural network, the adaptive topological region is selected. Using the erosion operation, the topological region shrinkage is achieved. The steerable filter based morphological self-organizing feature map neural network is applied to automatic target recognition of binary standard patterns and real-world infrared sequence images. Compared with Hamming network and morphological shared-weight networks respectively, the higher recognition correct rate, robust adaptability, quick training, and better generalization of the proposed method are achieved.

  20. Internal mechanisms underlying anticipatory language processing: Evidence from event-related-potentials and neural oscillations.

    Science.gov (United States)

    Li, Xiaoqing; Zhang, Yuping; Xia, Jinyan; Swaab, Tamara Y

    2017-07-28

    Although numerous studies have demonstrated that the language processing system can predict upcoming content during comprehension, there is still no clear picture of the anticipatory stage of predictive processing. This electroencephalograph study examined the cognitive and neural oscillatory mechanisms underlying anticipatory processing during language comprehension, and the consequences of this prediction for bottom-up processing of predicted/unpredicted content. Participants read Mandarin Chinese sentences that were either strongly or weakly constraining and that contained critical nouns that were congruent or incongruent with the sentence contexts. We examined the effects of semantic predictability on anticipatory processing prior to the onset of the critical nouns and on integration of the critical nouns. The results revealed that, at the integration stage, the strong-constraint condition (compared to the weak-constraint condition) elicited a reduced N400 and reduced theta activity (4-7Hz) for the congruent nouns, but induced beta (13-18Hz) and theta (4-7Hz) power decreases for the incongruent nouns, indicating benefits of confirmed predictions and potential costs of disconfirmed predictions. More importantly, at the anticipatory stage, the strongly constraining context elicited an enhanced sustained anterior negativity and beta power decrease (19-25Hz), which indicates that strong prediction places a higher processing load on the anticipatory stage of processing. The differences (in the ease of processing and the underlying neural oscillatory activities) between anticipatory and integration stages of lexical processing were discussed with regard to predictive processing models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network.

    Science.gov (United States)

    Del Papa, Bruno; Priesemann, Viola; Triesch, Jochen

    2017-01-01

    Many experiments have suggested that the brain operates close to a critical state, based on signatures of criticality such as power-law distributed neuronal avalanches. In neural network models, criticality is a dynamical state that maximizes information processing capacities, e.g. sensitivity to input, dynamical range and storage capacity, which makes it a favorable candidate state for brain function. Although models that self-organize towards a critical state have been proposed, the relation between criticality signatures and learning is still unclear. Here, we investigate signatures of criticality in a self-organizing recurrent neural network (SORN). Investigating criticality in the SORN is of particular interest because it has not been developed to show criticality. Instead, the SORN has been shown to exhibit spatio-temporal pattern learning through a combination of neural plasticity mechanisms and it reproduces a number of biological findings on neural variability and the statistics and fluctuations of synaptic efficacies. We show that, after a transient, the SORN spontaneously self-organizes into a dynamical state that shows criticality signatures comparable to those found in experiments. The plasticity mechanisms are necessary to attain that dynamical state, but not to maintain it. Furthermore, onset of external input transiently changes the slope of the avalanche distributions - matching recent experimental findings. Interestingly, the membrane noise level necessary for the occurrence of the criticality signatures reduces the model's performance in simple learning tasks. Overall, our work shows that the biologically inspired plasticity and homeostasis mechanisms responsible for the SORN's spatio-temporal learning abilities can give rise to criticality signatures in its activity when driven by random input, but these break down under the structured input of short repeating sequences.

  2. International language management and diversity climate in multicultural organizations

    DEFF Research Database (Denmark)

    Lauring, Jakob; Selmer, Jan

    2012-01-01

    Increasing globalization has made the use and management of language a vital element of engaging in international business activities. Despite this fact, empirical surveys with many respondents examining language management are extremely rare. Another equally important issue related to internatio......Increasing globalization has made the use and management of language a vital element of engaging in international business activities. Despite this fact, empirical surveys with many respondents examining language management are extremely rare. Another equally important issue related...... to internationalization is how to develop and support an environment that is tolerant of the diversity which exists in multicultural organizations. Based on questionnaire responses from 489 members of academic multicultural departments, we examined the relation between the management of a common language and a positive...... diversity climate. Results showed that consistency in English management communication had strong positive relationships with all of the four investigated diversity climate variables; openness to linguistic, visible, value, and informational diversity. English communication consistency had a positive...

  3. Neural constructivism or self-organization?

    NARCIS (Netherlands)

    van der Maas, H.L.J.; Molenaar, P.C.M.

    2000-01-01

    Comments on the article by S. R. Quartz et al (see record 1998-00749-001) which discussed the constructivist perspective of interaction between cognition and neural processes during development and consequences for theories of learning. Three arguments are given to show that neural constructivism

  4. Lexical processing and organization in bilingual first language acquisition: Guiding future research.

    Science.gov (United States)

    DeAnda, Stephanie; Poulin-Dubois, Diane; Zesiger, Pascal; Friend, Margaret

    2016-06-01

    A rich body of work in adult bilinguals documents an interconnected lexical network across languages, such that early word retrieval is language independent. This literature has yielded a number of influential models of bilingual semantic memory. However, extant models provide limited predictions about the emergence of lexical organization in bilingual first language acquisition (BFLA). Empirical evidence from monolingual infants suggests that lexical networks emerge early in development as children integrate phonological and semantic information. These findings tell us little about the interaction between 2 languages in early bilingual memory. To date, an understanding of when and how languages interact in early bilingual development is lacking. In this literature review, we present research documenting lexical-semantic development across monolingual and bilingual infants. This is followed by a discussion of current models of bilingual language representation and organization and their ability to account for the available empirical evidence. Together, these theoretical and empirical accounts inform and highlight unexplored areas of research and guide future work on early bilingual memory. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  5. Native-language N400 and P600 predict dissociable language-learning abilities in adults

    Science.gov (United States)

    Qi, Zhenghan; Beach, Sara D.; Finn, Amy S.; Minas, Jennifer; Goetz, Calvin; Chan, Brian; Gabrieli, John D.E.

    2018-01-01

    Language learning aptitude during adulthood varies markedly across individuals. An individual’s native-language ability has been associated with success in learning a new language as an adult. However, little is known about how native-language processing affects learning success and what neural markers of native-language processing, if any, are related to success in learning. We therefore related variation in electrophysiology during native-language processing to success in learning a novel artificial language. Event-related potentials (ERPs) were recorded while native English speakers judged the acceptability of English sentences prior to learning an artificial language. There was a trend towards a double dissociation between native-language ERPs and their relationships to novel syntax and vocabulary learning. Individuals who exhibited a greater N400 effect when processing English semantics showed better future learning of the artificial language overall. The N400 effect was related to syntax learning via its specific relationship to vocabulary learning. In contrast, the P600 effect size when processing English syntax predicted future syntax learning but not vocabulary learning. These findings show that distinct neural signatures of native-language processing relate to dissociable abilities for learning novel semantic and syntactic information. PMID:27737775

  6. Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human--Robot Interaction

    Directory of Open Access Journals (Sweden)

    Tatsuro Yamada

    2016-07-01

    Full Text Available To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language--behavior relationships and the temporal patterns of interaction. Here, ``internal dynamics'' refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language--behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language--behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

  7. Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human-Robot Interaction.

    Science.gov (United States)

    Yamada, Tatsuro; Murata, Shingo; Arie, Hiroaki; Ogata, Tetsuya

    2016-01-01

    To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language-behavior relationships and the temporal patterns of interaction. Here, "internal dynamics" refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human's linguistic instruction. After learning, the network actually formed the attractor structure representing both language-behavior relationships and the task's temporal pattern in its internal dynamics. In the dynamics, language-behavior mapping was achieved by the branching structure. Repetition of human's instruction and robot's behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.

  8. Quantitative analysis of volatile organic compounds using ion mobility spectra and cascade correlation neural networks

    Science.gov (United States)

    Harrington, Peter DEB.; Zheng, Peng

    1995-01-01

    Ion Mobility Spectrometry (IMS) is a powerful technique for trace organic analysis in the gas phase. Quantitative measurements are difficult, because IMS has a limited linear range. Factors that may affect the instrument response are pressure, temperature, and humidity. Nonlinear calibration methods, such as neural networks, may be ideally suited for IMS. Neural networks have the capability of modeling complex systems. Many neural networks suffer from long training times and overfitting. Cascade correlation neural networks train at very fast rates. They also build their own topology, that is a number of layers and number of units in each layer. By controlling the decay parameter in training neural networks, reproducible and general models may be obtained.

  9. Limitations to Plasticity of Language Network Reorganization in Localization Related Epilepsy

    Science.gov (United States)

    Mbwana, J.; Berl, M. M.; Ritzl, E. K.; Rosenberger, L.; Mayo, J.; Weinstein, S.; Conry, J. A.; Pearl, P. L.; Shamim, S.; Moore, E. N.; Sato, S.; Vezina, L. G.; Theodore, W. H.; Gaillard, W. D.

    2009-01-01

    Neural networks for processing language often are reorganized in patients with epilepsy. However, the extent and location of within and between hemisphere re-organization are not established. We studied 45 patients, all with a left hemisphere seizure focus (mean age 22.8, seizure onset 13.3), and 19 normal controls (mean age 24.8) with an fMRI…

  10. Invertebrate diversity classification using self-organizing map neural network: with some special topological functions

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2014-06-01

    Full Text Available In present study we used self-organizing map (SOM neural network to conduct the non-supervisory clustering of invertebrate orders in rice field. Four topological functions, i.e., cossintopf, sincostopf, acossintopf, and expsintopf, established on the template in toolbox of Matlab, were used in SOM neural network learning. Results showed that clusters were different when using different topological functions because different topological functions will generate different spatial structure of neurons in neural network. We may chose these functions and results based on comparison with the practical situation.

  11. Language and Recursion

    Science.gov (United States)

    Lowenthal, Francis

    2010-11-01

    This paper examines whether the recursive structure imbedded in some exercises used in the Non Verbal Communication Device (NVCD) approach is actually the factor that enables this approach to favor language acquisition and reacquisition in the case of children with cerebral lesions. For that a definition of the principle of recursion as it is used by logicians is presented. The two opposing approaches to the problem of language development are explained. For many authors such as Chomsky [1] the faculty of language is innate. This is known as the Standard Theory; the other researchers in this field, e.g. Bates and Elman [2], claim that language is entirely constructed by the young child: they thus speak of Language Acquisition. It is also shown that in both cases, a version of the principle of recursion is relevant for human language. The NVCD approach is defined and the results obtained in the domain of language while using this approach are presented: young subjects using this approach acquire a richer language structure or re-acquire such a structure in the case of cerebral lesions. Finally it is shown that exercises used in this framework imply the manipulation of recursive structures leading to regular grammars. It is thus hypothesized that language development could be favored using recursive structures with the young child. It could also be the case that the NVCD like exercises used with children lead to the elaboration of a regular language, as defined by Chomsky [3], which could be sufficient for language development but would not require full recursion. This double claim could reconcile Chomsky's approach with psychological observations made by adherents of the Language Acquisition approach, if it is confirmed by researches combining the use of NVCDs, psychometric methods and the use of Neural Networks. This paper thus suggests that a research group oriented towards this problematic should be organized.

  12. Neural reuse of action perception circuits for language, concepts and communication.

    Science.gov (United States)

    Pulvermüller, Friedemann

    2018-01-01

    Neurocognitive and neurolinguistics theories make explicit statements relating specialized cognitive and linguistic processes to specific brain loci. These linking hypotheses are in need of neurobiological justification and explanation. Recent mathematical models of human language mechanisms constrained by fundamental neuroscience principles and established knowledge about comparative neuroanatomy offer explanations for where, when and how language is processed in the human brain. In these models, network structure and connectivity along with action- and perception-induced correlation of neuronal activity co-determine neurocognitive mechanisms. Language learning leads to the formation of action perception circuits (APCs) with specific distributions across cortical areas. Cognitive and linguistic processes such as speech production, comprehension, verbal working memory and prediction are modelled by activity dynamics in these APCs, and combinatorial and communicative-interactive knowledge is organized in the dynamics within, and connections between APCs. The network models and, in particular, the concept of distributionally-specific circuits, can account for some previously not well understood facts about the cortical 'hubs' for semantic processing and the motor system's role in language understanding and speech sound recognition. A review of experimental data evaluates predictions of the APC model and alternative theories, also providing detailed discussion of some seemingly contradictory findings. Throughout, recent disputes about the role of mirror neurons and grounded cognition in language and communication are assessed critically. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

  13. Visual cortex entrains to sign language.

    Science.gov (United States)

    Brookshire, Geoffrey; Lu, Jenny; Nusbaum, Howard C; Goldin-Meadow, Susan; Casasanto, Daniel

    2017-06-13

    Despite immense variability across languages, people can learn to understand any human language, spoken or signed. What neural mechanisms allow people to comprehend language across sensory modalities? When people listen to speech, electrophysiological oscillations in auditory cortex entrain to slow ([Formula: see text]8 Hz) fluctuations in the acoustic envelope. Entrainment to the speech envelope may reflect mechanisms specialized for auditory perception. Alternatively, flexible entrainment may be a general-purpose cortical mechanism that optimizes sensitivity to rhythmic information regardless of modality. Here, we test these proposals by examining cortical coherence to visual information in sign language. First, we develop a metric to quantify visual change over time. We find quasiperiodic fluctuations in sign language, characterized by lower frequencies than fluctuations in speech. Next, we test for entrainment of neural oscillations to visual change in sign language, using electroencephalography (EEG) in fluent speakers of American Sign Language (ASL) as they watch videos in ASL. We find significant cortical entrainment to visual oscillations in sign language sign is strongest over occipital and parietal cortex, in contrast to speech, where coherence is strongest over the auditory cortex. Nonsigners also show coherence to sign language, but entrainment at frontal sites is reduced relative to fluent signers. These results demonstrate that flexible cortical entrainment to language does not depend on neural processes that are specific to auditory speech perception. Low-frequency oscillatory entrainment may reflect a general cortical mechanism that maximizes sensitivity to informational peaks in time-varying signals.

  14. Prediction of ozone tropospheric degradation rate constant of organic compounds by using artificial neural networks

    International Nuclear Information System (INIS)

    Fatemi, M.H.

    2006-01-01

    Ozone tropospheric degradation of organic compound is very important in environmental chemistry. The lifetime of organic chemicals in the atmosphere can be calculated from the knowledge of the rate constant of their reaction with free radicals such as OH and NO 3 or O 3 . In the present work, the rate constant for the tropospheric degradation of 137 organic compounds by reaction with ozone, the least widely and successfully modeled degradation process, are predicted by quantitative structure activity relationships modeling based on a variety of theoretical descriptors, which screened and selected by genetic algorithm variable subset selection procedure. These descriptors which can be used as inputs for generated artificial neural networks are; HOMO-LUMO gap, number of double bonds, number of single bonds, maximum net charge on C atom, minimum (>0.1) bond order of C atom and Minimum e-e repulsion of H atom. After generation, optimization and training of artificial neural network, network was used for the prediction of log KO 3 for the validation set. The root mean square error for the neural network calculated log KO 3 for training, prediction and validation set are 0.357, 0.460 and 0.481, respectively, which are smaller than those obtained by multiple linear regressions model (1.217, 0.870 and 0.968, respectively). Results obtained reveal the reliability and good predictivity of neural network model for the prediction of ozone tropospheric degradations rate constant of organic compounds

  15. Homotopic organization of essential language sites in right and bilateral cerebral hemispheric dominance.

    Science.gov (United States)

    Chang, Edward F; Wang, Doris D; Perry, David W; Barbaro, Nicholas M; Berger, Mitchel S

    2011-04-01

    Language dominance in the right hemisphere is rare. Therefore, the organization of essential language sites in the dominant right hemisphere is unclear, especially compared with cases involving the more prevalent left dominant hemisphere. The authors reviewed the medical records of 15 patients who underwent awake craniotomy for tumor or epilepsy surgery and speech mapping of right hemisphere perisylvian language areas at the University of California, San Francisco. All patients were determined to have either complete right-sided or bilateral language dominance by preoperative Wada testing. All patients but one were left-handed. Of more than 331 total stimulation sites, 27 total sites were identified as essential for language function (14 sites for speech arrest/anarthria; 12 for anomia; and 1 for alexia). While significant interindividual variability was observed, the general pattern of language organization was similar to classic descriptions of frontal language production and posterior temporal language integration for the left hemisphere. Speech arrest sites were clustered in the ventral precentral gyrus and pars opercularis. Anomia sites were more widely distributed, but were focused in the posterior superior and middle temporal gyri as well as the inferior parietal gyrus. One alexia site was found over the superior temporal gyrus. Face sensory and motor cortical sites were also identified along the ventral sensorimotor strip. The prevalence and specificity of essential language sites were greater in unilateral right hemisphere-dominant patients, compared with those with bilateral dominance by Wada testing. The authors' results suggest that the organization of language in right hemisphere dominance mirrors that of left hemisphere dominance. Awake speech mapping is a safe and reliable surgical adjunct in these rare clinical cases and should be done in the setting of right hemisphere dominance to avoid preventable postoperative aphasia.

  16. Image Fusion Based on the Self-Organizing Feature Map Neural Networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Zhaoli; SUN Shenghe

    2001-01-01

    This paper presents a new image datafusion scheme based on the self-organizing featuremap (SOFM) neural networks.The scheme consists ofthree steps:(1) pre-processing of the images,whereweighted median filtering removes part of the noisecomponents corrupting the image,(2) pixel clusteringfor each image using two-dimensional self-organizingfeature map neural networks,and (3) fusion of the im-ages obtained in Step (2) utilizing fuzzy logic,whichsuppresses the residual noise components and thusfurther improves the image quality.It proves thatsuch a three-step combination offers an impressive ef-fectiveness and performance improvement,which isconfirmed by simulations involving three image sen-sors (each of which has a different noise structure).

  17. Native-language N400 and P600 predict dissociable language-learning abilities in adults.

    Science.gov (United States)

    Qi, Zhenghan; Beach, Sara D; Finn, Amy S; Minas, Jennifer; Goetz, Calvin; Chan, Brian; Gabrieli, John D E

    2017-04-01

    Language learning aptitude during adulthood varies markedly across individuals. An individual's native-language ability has been associated with success in learning a new language as an adult. However, little is known about how native-language processing affects learning success and what neural markers of native-language processing, if any, are related to success in learning. We therefore related variation in electrophysiology during native-language processing to success in learning a novel artificial language. Event-related potentials (ERPs) were recorded while native English speakers judged the acceptability of English sentences prior to learning an artificial language. There was a trend towards a double dissociation between native-language ERPs and their relationships to novel syntax and vocabulary learning. Individuals who exhibited a greater N400 effect when processing English semantics showed better future learning of the artificial language overall. The N400 effect was related to syntax learning via its specific relationship to vocabulary learning. In contrast, the P600 effect size when processing English syntax predicted future syntax learning but not vocabulary learning. These findings show that distinct neural signatures of native-language processing relate to dissociable abilities for learning novel semantic and syntactic information. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Music and Language Syntax Interact in Broca's Area: An fMRI Study.

    Directory of Open Access Journals (Sweden)

    Richard Kunert

    Full Text Available Instrumental music and language are both syntactic systems, employing complex, hierarchically-structured sequences built using implicit structural norms. This organization allows listeners to understand the role of individual words or tones in the context of an unfolding sentence or melody. Previous studies suggest that the brain mechanisms of syntactic processing may be partly shared between music and language. However, functional neuroimaging evidence for anatomical overlap of brain activity involved in linguistic and musical syntactic processing has been lacking. In the present study we used functional magnetic resonance imaging (fMRI in conjunction with an interference paradigm based on sung sentences. We show that the processing demands of musical syntax (harmony and language syntax interact in Broca's area in the left inferior frontal gyrus (without leading to music and language main effects. A language main effect in Broca's area only emerged in the complex music harmony condition, suggesting that (with our stimuli and tasks a language effect only becomes visible under conditions of increased demands on shared neural resources. In contrast to previous studies, our design allows us to rule out that the observed neural interaction is due to: (1 general attention mechanisms, as a psychoacoustic auditory anomaly behaved unlike the harmonic manipulation, (2 error processing, as the language and the music stimuli contained no structural errors. The current results thus suggest that two different cognitive domains-music and language-might draw on the same high level syntactic integration resources in Broca's area.

  19. The impact of iconic gestures on foreign language word learning and its neural substrate.

    Science.gov (United States)

    Macedonia, Manuela; Müller, Karsten; Friederici, Angela D

    2011-06-01

    Vocabulary acquisition represents a major challenge in foreign language learning. Research has demonstrated that gestures accompanying speech have an impact on memory for verbal information in the speakers' mother tongue and, as recently shown, also in foreign language learning. However, the neural basis of this effect remains unclear. In a within-subjects design, we compared learning of novel words coupled with iconic and meaningless gestures. Iconic gestures helped learners to significantly better retain the verbal material over time. After the training, participants' brain activity was registered by means of fMRI while performing a word recognition task. Brain activations to words learned with iconic and with meaningless gestures were contrasted. We found activity in the premotor cortices for words encoded with iconic gestures. In contrast, words encoded with meaningless gestures elicited a network associated with cognitive control. These findings suggest that memory performance for newly learned words is not driven by the motor component as such, but by the motor image that matches an underlying representation of the word's semantics. Copyright © 2010 Wiley-Liss, Inc.

  20. Cracking the neural code, treating paralysis and the future of bioelectronic medicine.

    Science.gov (United States)

    Bouton, C

    2017-07-01

    The human nervous system is a vast network carrying not only sensory and movement information, but also information to and from our organs, intimately linking it to our overall health. Scientists and engineers have been working for decades to tap into this network and 'crack the neural code' by decoding neural signals and learning how to 'speak' the language of the nervous system. Progress has been made in developing neural decoding methods to decipher brain activity and bioelectronic technologies to treat rheumatoid arthritis, paralysis, epilepsy and for diagnosing brain-related diseases such as Parkinson's and Alzheimer's disease. In a recent first-in-human study involving paralysis, a paralysed male study participant regained movement in his hand, years after his injury, through the use of a bioelectronic neural bypass. This work combined neural decoding and neurostimulation methods to translate and re-route signals around damaged neural pathways within the central nervous system. By extending these methods to decipher neural messages in the peripheral nervous system, status information from our bodily functions and specific organs could be gained. This, one day, could allow real-time diagnostics to be performed to give us a deeper insight into a patient's condition, or potentially even predict disease or allow early diagnosis. The future of bioelectronic medicine is extremely bright and is wide open as new diagnostic and treatment options are developed for patients around the world. © 2017 The Association for the Publication of the Journal of Internal Medicine.

  1. Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network.

    Science.gov (United States)

    Han, Hong-Gui; Zhang, Lu; Hou, Ying; Qiao, Jun-Fei

    2016-02-01

    A nonlinear model predictive control (NMPC) scheme is developed in this paper based on a self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure and parameters are adjusted concurrently in the training process. The proposed SR-RBF neural network is represented in a general nonlinear form for predicting the future dynamic behaviors of nonlinear systems. To improve the modeling accuracy, a spiking-based growing and pruning algorithm and an adaptive learning algorithm are developed to tune the structure and parameters of the SR-RBF neural network, respectively. Meanwhile, for the control problem, an improved gradient method is utilized for the solution of the optimization problem in NMPC. The stability of the resulting control system is proved based on the Lyapunov stability theory. Finally, the proposed SR-RBF neural network-based NMPC (SR-RBF-NMPC) is used to control the dissolved oxygen (DO) concentration in a wastewater treatment process (WWTP). Comparisons with other existing methods demonstrate that the SR-RBF-NMPC can achieve a considerably better model fitting for WWTP and a better control performance for DO concentration.

  2. Second language processing : when are first and second languages processed similarly?

    NARCIS (Netherlands)

    Sabourin, Laura; Stowe, Laurie A.

    In this article we investigate the effects of first language (L1) on second language (L2) neural processing for two grammatical constructions (verbal domain dependency and grammatical gender), focusing on the event-related potential P600 effect, which has been found in both L1 and L2 processing.

  3. Stages of didactic games organizing in junior pupils’ foreign language teaching

    Directory of Open Access Journals (Sweden)

    Tamara Marchii-Dmytrash

    2017-02-01

    Full Text Available The feasibility of didactic games using as a method of educational activity organizingand learning of a foreign language in primary school in the context of realization theregularity and consistency principle are justified in the article. It is concretized the stages ofdidactic games organizing in foreign language teaching (preparatory, executive, analyticalcorrectiveand the tasks of each of them, and the impact of didactic games on the forming ofjunior pupils’ foreign language knowledge are defined.Key words: didactic game, method, educational activity, primary school, foreignlanguage, junior pupils, stages.

  4. Nonlinear dynamics analysis of a self-organizing recurrent neural network: chaos waning.

    Science.gov (United States)

    Eser, Jürgen; Zheng, Pengsheng; Triesch, Jochen

    2014-01-01

    Self-organization is thought to play an important role in structuring nervous systems. It frequently arises as a consequence of plasticity mechanisms in neural networks: connectivity determines network dynamics which in turn feed back on network structure through various forms of plasticity. Recently, self-organizing recurrent neural network models (SORNs) have been shown to learn non-trivial structure in their inputs and to reproduce the experimentally observed statistics and fluctuations of synaptic connection strengths in cortex and hippocampus. However, the dynamics in these networks and how they change with network evolution are still poorly understood. Here we investigate the degree of chaos in SORNs by studying how the networks' self-organization changes their response to small perturbations. We study the effect of perturbations to the excitatory-to-excitatory weight matrix on connection strengths and on unit activities. We find that the network dynamics, characterized by an estimate of the maximum Lyapunov exponent, becomes less chaotic during its self-organization, developing into a regime where only few perturbations become amplified. We also find that due to the mixing of discrete and (quasi-)continuous variables in SORNs, small perturbations to the synaptic weights may become amplified only after a substantial delay, a phenomenon we propose to call deferred chaos.

  5. Lifelong learning of human actions with deep neural network self-organization.

    Science.gov (United States)

    Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan

    2017-12-01

    Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences. The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns. We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields. Lifelong learning is achieved in terms of prediction-driven neural dynamics in which the growth and the adaptation of the recurrent networks are driven by their capability to reconstruct temporally ordered input sequences. Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions. Additional experiments show the ability of our model to adapt to non-stationary input avoiding catastrophic interference. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  6. Model of the Dynamic Construction Process of Texts and Scaling Laws of Words Organization in Language Systems.

    Science.gov (United States)

    Li, Shan; Lin, Ruokuang; Bian, Chunhua; Ma, Qianli D Y; Ivanov, Plamen Ch

    2016-01-01

    Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language.

  7. Model of the Dynamic Construction Process of Texts and Scaling Laws of Words Organization in Language Systems.

    Directory of Open Access Journals (Sweden)

    Shan Li

    Full Text Available Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language.

  8. Neural overlap of L1 and L2 semantic representations in speech : A decoding approach

    NARCIS (Netherlands)

    Van De Putte, Eowyn; De Baene, W.; Brass, Marcel; Duyck, Wouter

    2017-01-01

    Although research has now converged towards a consensus that both languages of a bilingual are represented in at least partly shared systems for language comprehension, it remains unclear whether both languages are represented in the same neural populations for production. We investigated the neural

  9. A neural model of figure-ground organization.

    Science.gov (United States)

    Craft, Edward; Schütze, Hartmut; Niebur, Ernst; von der Heydt, Rüdiger

    2007-06-01

    Psychophysical studies suggest that figure-ground organization is a largely autonomous process that guides--and thus precedes--allocation of attention and object recognition. The discovery of border-ownership representation in single neurons of early visual cortex has confirmed this view. Recent theoretical studies have demonstrated that border-ownership assignment can be modeled as a process of self-organization by lateral interactions within V2 cortex. However, the mechanism proposed relies on propagation of signals through horizontal fibers, which would result in increasing delays of the border-ownership signal with increasing size of the visual stimulus, in contradiction with experimental findings. It also remains unclear how the resulting border-ownership representation would interact with attention mechanisms to guide further processing. Here we present a model of border-ownership coding based on dedicated neural circuits for contour grouping that produce border-ownership assignment and also provide handles for mechanisms of selective attention. The results are consistent with neurophysiological and psychophysical findings. The model makes predictions about the hypothetical grouping circuits and the role of feedback between cortical areas.

  10. Tracking Typological Traits of Uralic Languages in Distributed Language Representations

    DEFF Research Database (Denmark)

    Bjerva, Johannes; Augenstein, Isabelle

    2018-01-01

    Although linguistic typology has a long history, computational approaches have only recently gained popularity. The use of distributed representations in computational linguistics has also become increasingly popular. A recent development is to learn distributed representations of language...... for model transfer between Uralic languages in deep neural networks. We then investigate which typological features are encoded in these representations by attempting to predict features in the World Atlas of Language Structures, at various stages of fine-tuning of the representations. We focus on Uralic...

  11. Neural signatures of second language learning and control.

    Science.gov (United States)

    Bartolotti, James; Bradley, Kailyn; Hernandez, Arturo E; Marian, Viorica

    2017-04-01

    Experience with multiple languages has unique effects on cortical structure and information processing. Differences in gray matter density and patterns of cortical activation are observed in lifelong bilinguals compared to monolinguals as a result of their experience managing interference across languages. Monolinguals who acquire a second language later in life begin to encounter the same type of linguistic interference as bilinguals, but with a different pre-existing language architecture. The current study used functional magnetic resonance imaging to explore the beginning stages of second language acquisition and cross-linguistic interference in monolingual adults. We found that after English monolinguals learned novel Spanish vocabulary, English and Spanish auditory words led to distinct patterns of cortical activation, with greater recruitment of posterior parietal regions in response to English words and of left hippocampus in response to Spanish words. In addition, cross-linguistic interference from English influenced processing of newly-learned Spanish words, decreasing hippocampus activity. Results suggest that monolinguals may rely on different memory systems to process a newly-learned second language, and that the second language system is sensitive to native language interference. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Organic Computing

    CERN Document Server

    Würtz, Rolf P

    2008-01-01

    Organic Computing is a research field emerging around the conviction that problems of organization in complex systems in computer science, telecommunications, neurobiology, molecular biology, ethology, and possibly even sociology can be tackled scientifically in a unified way. From the computer science point of view, the apparent ease in which living systems solve computationally difficult problems makes it inevitable to adopt strategies observed in nature for creating information processing machinery. In this book, the major ideas behind Organic Computing are delineated, together with a sparse sample of computational projects undertaken in this new field. Biological metaphors include evolution, neural networks, gene-regulatory networks, networks of brain modules, hormone system, insect swarms, and ant colonies. Applications are as diverse as system design, optimization, artificial growth, task allocation, clustering, routing, face recognition, and sign language understanding.

  13. Detecting resting-state functional connectivity in the language system using functional near-infrared spectroscopy

    Science.gov (United States)

    Zhang, Yu-Jin; Lu, Chun-Ming; Biswal, Bharat B.; Zang, Yu-Feng; Peng, Dan-Lin; Zhu, Chao-Zhe

    2010-07-01

    Functional connectivity has become one of the important approaches to understanding the functional organization of the human brain. Recently, functional near-infrared spectroscopy (fNIRS) was demonstrated as a feasible method to study resting-state functional connectivity (RSFC) in the sensory and motor systems. However, whether such fNIRS-based RSFC can be revealed in high-level and complex functional systems remains unknown. In the present study, the feasibility of such an approach is tested on the language system, of which the neural substrates have been well documented in the literature. After determination of a seed channel by a language localizer task, the correlation strength between the low frequency fluctuations of the fNIRS signal at the seed channel and those at all other channels is used to evaluate the language system RSFC. Our results show a significant RSFC between the left inferior frontal cortex and superior temporal cortex, components both associated with dominant language regions. Moreover, the RSFC map demonstrates left lateralization of the language system. In conclusion, the present study successfully utilized fNIRS-based RSFC to study a complex and high-level neural system, and provides further evidence for the validity of the fNIRS-based RSFC approach.

  14. The neural exploitation hypothesis and its implications for an embodied approach to language and cognition: Insights from the study of action verbs processing and motor disorders in Parkinson's disease.

    Science.gov (United States)

    Gallese, Vittorio; Cuccio, Valentina

    2018-03-01

    As it is widely known, Parkinson's disease is clinically characterized by motor disorders such as the loss of voluntary movement control, including resting tremor, postural instability, and bradykinesia (Bocanegra et al., 2015; Helmich, Hallett, Deuschl, Toni, & Bloem, 2012; Liu et al., 2006; Rosin, Topka, & Dichgans, 1997). In the last years, many empirical studies (e.g., Bocanegra et al., 2015; Spadacenta et al., 2012) have also shown that the processing of action verbs is selectively impaired in patients affected by this neurodegenerative disorder. In the light of these findings, it has been suggested that Parkinson disorder can be interpreted within an embodied cognition framework (e.g., Bocanegra et al., 2015). The central tenet of any embodied approach to language and cognition is that high order cognitive functions are grounded in the sensory-motor system. With regard to this point, Gallese (2008) proposed the neural exploitation hypothesis to account for, at the phylogenetic level, how key aspects of human language are underpinned by brain mechanisms originally evolved for sensory-motor integration. Glenberg and Gallese (2012) also applied the neural exploitation hypothesis to the ontogenetic level. On the basis of these premises, they developed a theory of language acquisition according to which, sensory-motor mechanisms provide a neurofunctional architecture for the acquisition of language, while retaining their original functions as well. The neural exploitation hypothesis is here applied to interpret the profile of patients affected by Parkinson's disease. It is suggested that action semantic impairments directly tap onto motor disorders. Finally, a discussion of what theory of language is needed to account for the interactions between language and movement disorders is presented. Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. Neural oscillatory mechanisms during novel grammar learning underlying language analytical abilities.

    Science.gov (United States)

    Kepinska, Olga; Pereda, Ernesto; Caspers, Johanneke; Schiller, Niels O

    2017-12-01

    The goal of the present study was to investigate the initial phases of novel grammar learning on a neural level, concentrating on mechanisms responsible for individual variability between learners. Two groups of participants, one with high and one with average language analytical abilities, performed an Artificial Grammar Learning (AGL) task consisting of learning and test phases. During the task, EEG signals from 32 cap-mounted electrodes were recorded and epochs corresponding to the learning phases were analysed. We investigated spectral power modulations over time, and functional connectivity patterns by means of a bivariate, frequency-specific index of phase synchronization termed Phase Locking Value (PLV). Behavioural data showed learning effects in both groups, with a steeper learning curve and higher ultimate attainment for the highly skilled learners. Moreover, we established that cortical connectivity patterns and profiles of spectral power modulations over time differentiated L2 learners with various levels of language analytical abilities. Over the course of the task, the learning process seemed to be driven by whole-brain functional connectivity between neuronal assemblies achieved by means of communication in the beta band frequency. On a shorter time-scale, increasing proficiency on the AGL task appeared to be supported by stronger local synchronisation within the right hemisphere regions. Finally, we observed that the highly skilled learners might have exerted less mental effort, or reduced attention for the task at hand once the learning was achieved, as evidenced by the higher alpha band power. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

    Directory of Open Access Journals (Sweden)

    Sheng-Jun Wang

    2011-06-01

    Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

  17. Onset age of L2 acquisition influences language network in early and late Cantonese-Mandarin bilinguals.

    Science.gov (United States)

    Liu, Xiaojin; Tu, Liu; Wang, Junjing; Jiang, Bo; Gao, Wei; Pan, Ximin; Li, Meng; Zhong, Miao; Zhu, Zhenzhen; Niu, Meiqi; Li, Yanyan; Zhao, Ling; Chen, Xiaoxi; Liu, Chang; Lu, Zhi; Huang, Ruiwang

    2017-11-01

    Early second language (L2) experience influences the neural organization of L2 in neuro-plastic terms. Previous studies tried to reveal these plastic effects of age of second language acquisition (AoA-L2) and proficiency-level in L2 (PL-L2) on the neural basis of language processing in bilinguals. Although different activation patterns have been observed during language processing in early and late bilinguals by task-fMRI, few studies reported the effect of AoA-L2 and high PL-L2 on language network at resting state. In this study, we acquired resting-state fMRI (R-fMRI) data from 10 Cantonese (L1)-Mandarin (L2) early bilinguals (acquired L2: 3years old) and 11 late bilinguals (acquired L2: 6years old), and analyzed their topological properties of language networks after controlling the language daily exposure and usage as well as PL in L1 and L2. We found that early bilinguals had significantly a higher clustering coefficient, global and local efficiency, but significantly lower characteristic path length compared to late bilinguals. Modular analysis indicated that compared to late bilinguals, early bilinguals showed significantly stronger intra-modular functional connectivity in the semantic and phonetic modules, stronger inter-modular functional connectivity between the semantic and phonetic modules as well as between the phonetic and syntactic modules. Differences in global and local parameters may reflect different patterns of neuro-plasticity respectively for early and late bilinguals. These results suggested that different L2 experience influences topological properties of language network, even if late bilinguals achieve high PL-L2. Our findings may provide a new perspective of neural mechanisms related to early and late bilinguals. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. 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)

  19. Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm

    Directory of Open Access Journals (Sweden)

    Haizhou Wu

    2016-01-01

    Full Text Available Symbiotic organisms search (SOS is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a challenging task to present a satisfactory and efficient training algorithm for feedforward neural networks (FNNs. In this paper, SOS is employed as a new method for training FNNs. To investigate the performance of the aforementioned method, eight different datasets selected from the UCI machine learning repository are employed for experiment and the results are compared among seven metaheuristic algorithms. The results show that SOS performs better than other algorithms for training FNNs in terms of converging speed. It is also proven that an FNN trained by the method of SOS has better accuracy than most algorithms compared.

  20. Collaborative Recurrent Neural Networks forDynamic Recommender Systems

    Science.gov (United States)

    2016-11-22

    JMLR: Workshop and Conference Proceedings 63:366–381, 2016 ACML 2016 Collaborative Recurrent Neural Networks for Dynamic Recommender Systems Young...an unprece- dented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating...Recurrent Neural Network, Recommender System , Neural Language Model, Collaborative Filtering 1. Introduction As ever larger parts of the population

  1. 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.

  2. Neural processing of speech in children is influenced by bilingual experience

    Science.gov (United States)

    Krizman, Jennifer; Slater, Jessica; Skoe, Erika; Marian, Viorica; Kraus, Nina

    2014-01-01

    Language experience fine-tunes how the auditory system processes sound. For example, bilinguals, relative to monolinguals, have more robust evoked responses to speech that manifest as stronger neural encoding of the fundamental frequency (F0) and greater across-trial consistency. However, it is unknown whether such enhancements increase with increasing second language experience. We predict that F0 amplitude and neural consistency scale with dual-language experience during childhood, such that more years of bilingual experience leads to more robust F0 encoding and greater neural consistency. To test this hypothesis, we recorded auditory brainstem responses to the synthesized syllables ‘ba’ and ‘ga’ in two groups of bilingual children who were matched for age at test (8.4+/−0.67 years) but differed in their age of second language acquisition. One group learned English and Spanish simultaneously from birth (n=13), while the second group learned the two languages sequentially (n=15), spending on average their first four years as monolingual Spanish speakers. We find that simultaneous bilinguals have a larger F0 response to ‘ba’ and ‘ga’ and a more consistent response to ‘ba’ compared to sequential bilinguals. We also demonstrate that these neural enhancements positively relate with years of bilingual experience. These findings support the notion that bilingualism enhances subcortical auditory processing. PMID:25445377

  3. Neural modularity helps organisms evolve to learn new skills without forgetting old skills.

    Science.gov (United States)

    Ellefsen, Kai Olav; Mouret, Jean-Baptiste; Clune, Jeff

    2015-04-01

    A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to

  4. Neural modularity helps organisms evolve to learn new skills without forgetting old skills.

    Directory of Open Access Journals (Sweden)

    Kai Olav Ellefsen

    2015-04-01

    Full Text Available A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand. To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1 that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2 that one benefit of the modularity ubiquitous in the brains of natural animals

  5. Neural Modularity Helps Organisms Evolve to Learn New Skills without Forgetting Old Skills

    Science.gov (United States)

    Ellefsen, Kai Olav; Mouret, Jean-Baptiste; Clune, Jeff

    2015-01-01

    A long-standing goal in artificial intelligence is creating agents that can learn a variety of different skills for different problems. In the artificial intelligence subfield of neural networks, a barrier to that goal is that when agents learn a new skill they typically do so by losing previously acquired skills, a problem called catastrophic forgetting. That occurs because, to learn the new task, neural learning algorithms change connections that encode previously acquired skills. How networks are organized critically affects their learning dynamics. In this paper, we test whether catastrophic forgetting can be reduced by evolving modular neural networks. Modularity intuitively should reduce learning interference between tasks by separating functionality into physically distinct modules in which learning can be selectively turned on or off. Modularity can further improve learning by having a reinforcement learning module separate from sensory processing modules, allowing learning to happen only in response to a positive or negative reward. In this paper, learning takes place via neuromodulation, which allows agents to selectively change the rate of learning for each neural connection based on environmental stimuli (e.g. to alter learning in specific locations based on the task at hand). To produce modularity, we evolve neural networks with a cost for neural connections. We show that this connection cost technique causes modularity, confirming a previous result, and that such sparsely connected, modular networks have higher overall performance because they learn new skills faster while retaining old skills more and because they have a separate reinforcement learning module. Our results suggest (1) that encouraging modularity in neural networks may help us overcome the long-standing barrier of networks that cannot learn new skills without forgetting old ones, and (2) that one benefit of the modularity ubiquitous in the brains of natural animals might be to

  6. Program Helps Simulate Neural Networks

    Science.gov (United States)

    Villarreal, James; Mcintire, Gary

    1993-01-01

    Neural Network Environment on Transputer System (NNETS) computer program provides users high degree of flexibility in creating and manipulating wide variety of neural-network topologies at processing speeds not found in conventional computing environments. Supports back-propagation and back-propagation-related algorithms. Back-propagation algorithm used is implementation of Rumelhart's generalized delta rule. NNETS developed on INMOS Transputer(R). Predefines back-propagation network, Jordan network, and reinforcement network to assist users in learning and defining own networks. Also enables users to configure other neural-network paradigms from NNETS basic architecture. Small portion of software written in OCCAM(R) language.

  7. Prediction of pelvic organ prolapse using an artificial neural network.

    Science.gov (United States)

    Robinson, Christopher J; Swift, Steven; Johnson, Donna D; Almeida, Jonas S

    2008-08-01

    The objective of this investigation was to test the ability of a feedforward artificial neural network (ANN) to differentiate patients who have pelvic organ prolapse (POP) from those who retain good pelvic organ support. Following institutional review board approval, patients with POP (n = 87) and controls with good pelvic organ support (n = 368) were identified from the urogynecology research database. Historical and clinical information was extracted from the database. Data analysis included the training of a feedforward ANN, variable selection, and external validation of the model with an independent data set. Twenty variables were used. The median-performing ANN model used a median of 3 (quartile 1:3 to quartile 3:5) variables and achieved an area under the receiver operator curve of 0.90 (external, independent validation set). Ninety percent sensitivity and 83% specificity were obtained in the external validation by ANN classification. Feedforward ANN modeling is applicable to the identification and prediction of POP.

  8. δ-Protocadherins: Organizers of neural circuit assembly.

    Science.gov (United States)

    Light, Sarah E W; Jontes, James D

    2017-09-01

    The δ-protocadherins comprise a small family of homophilic cell adhesion molecules within the larger cadherin superfamily. They are essential for neural development as mutations in these molecules give rise to human neurodevelopmental disorders, such as schizophrenia and epilepsy, and result in behavioral defects in animal models. Despite their importance to neural development, a detailed understanding of their mechanisms and the ways in which their loss leads to changes in neural function is lacking. However, recent results have begun to reveal roles for the δ-protocadherins in both regulation of neurogenesis and lineage-dependent circuit assembly, as well as in contact-dependent motility and selective axon fasciculation. These evolutionarily conserved mechanisms could have a profound impact on the robust assembly of the vertebrate nervous system. Future work should be focused on unraveling the molecular mechanisms of the δ-protocadherins and understanding how this family functions broadly to regulate neural development. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Graph theoretical analysis of functional network for comprehension of sign language.

    Science.gov (United States)

    Liu, Lanfang; Yan, Xin; Liu, Jin; Xia, Mingrui; Lu, Chunming; Emmorey, Karen; Chu, Mingyuan; Ding, Guosheng

    2017-09-15

    Signed languages are natural human languages using the visual-motor modality. Previous neuroimaging studies based on univariate activation analysis show that a widely overlapped cortical network is recruited regardless whether the sign language is comprehended (for signers) or not (for non-signers). Here we move beyond previous studies by examining whether the functional connectivity profiles and the underlying organizational structure of the overlapped neural network may differ between signers and non-signers when watching sign language. Using graph theoretical analysis (GTA) and fMRI, we compared the large-scale functional network organization in hearing signers with non-signers during the observation of sentences in Chinese Sign Language. We found that signed sentences elicited highly similar cortical activations in the two groups of participants, with slightly larger responses within the left frontal and left temporal gyrus in signers than in non-signers. Crucially, further GTA revealed substantial group differences in the topologies of this activation network. Globally, the network engaged by signers showed higher local efficiency (t (24) =2.379, p=0.026), small-worldness (t (24) =2.604, p=0.016) and modularity (t (24) =3.513, p=0.002), and exhibited different modular structures, compared to the network engaged by non-signers. Locally, the left ventral pars opercularis served as a network hub in the signer group but not in the non-signer group. These findings suggest that, despite overlap in cortical activation, the neural substrates underlying sign language comprehension are distinguishable at the network level from those for the processing of gestural action. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Neural coding in graphs of bidirectional associative memories.

    Science.gov (United States)

    Bouchain, A David; Palm, Günther

    2012-01-24

    In the last years we have developed large neural network models for the realization of complex cognitive tasks in a neural network architecture that resembles the network of the cerebral cortex. We have used networks of several cortical modules that contain two populations of neurons (one excitatory, one inhibitory). The excitatory populations in these so-called "cortical networks" are organized as a graph of Bidirectional Associative Memories (BAMs), where edges of the graph correspond to BAMs connecting two neural modules and nodes of the graph correspond to excitatory populations with associative feedback connections (and inhibitory interneurons). The neural code in each of these modules consists essentially of the firing pattern of the excitatory population, where mainly it is the subset of active neurons that codes the contents to be represented. The overall activity can be used to distinguish different properties of the patterns that are represented which we need to distinguish and control when performing complex tasks like language understanding with these cortical networks. The most important pattern properties or situations are: exactly fitting or matching input, incomplete information or partially matching pattern, superposition of several patterns, conflicting information, and new information that is to be learned. We show simple simulations of these situations in one area or module and discuss how to distinguish these situations based on the overall internal activation of the module. This article is part of a Special Issue entitled "Neural Coding". Copyright © 2011 Elsevier B.V. All rights reserved.

  11. Effects of Some Neurobiological Factors in a Self-organized Critical Model Based on Neural Networks

    International Nuclear Information System (INIS)

    Zhou Liming; Zhang Yingyue; Chen Tianlun

    2005-01-01

    Based on an integrate-and-fire mechanism, we investigate the effect of changing the efficacy of the synapse, the transmitting time-delayed, and the relative refractoryperiod on the self-organized criticality in our neural network model.

  12. The neural basis of speech sound discrimination from infancy to adulthood

    OpenAIRE

    Partanen, Eino

    2013-01-01

    Rapid processing of speech is facilitated by neural representations of native language phonemes. However, some disorders and developmental conditions, such as developmental dyslexia, can hamper the development of these neural memory traces, leading to language delays and poor academic achievement. While the early identification of such deficits is paramount so that interventions can be started as early as possible, there is currently no systematically used ecologically valid paradigm for the ...

  13. ANT Advanced Neural Tool

    Energy Technology Data Exchange (ETDEWEB)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-07-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs.

  14. ANT Advanced Neural Tool

    International Nuclear Information System (INIS)

    Labrador, I.; Carrasco, R.; Martinez, L.

    1996-01-01

    This paper describes a practical introduction to the use of Artificial Neural Networks. Artificial Neural Nets are often used as an alternative to the traditional symbolic manipulation and first order logic used in Artificial Intelligence, due the high degree of difficulty to solve problems that can not be handled by programmers using algorithmic strategies. As a particular case of Neural Net a Multilayer Perception developed by programming in C language on OS9 real time operating system is presented. A detailed description about the program structure and practical use are included. Finally, several application examples that have been treated with the tool are presented, and some suggestions about hardware implementations. (Author) 15 refs

  15. 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.

  16. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

    Science.gov (United States)

    Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

    2010-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  17. Probabilistic language models in cognitive neuroscience: Promises and pitfalls.

    Science.gov (United States)

    Armeni, Kristijan; Willems, Roel M; Frank, Stefan L

    2017-12-01

    Cognitive neuroscientists of language comprehension study how neural computations relate to cognitive computations during comprehension. On the cognitive part of the equation, it is important that the computations and processing complexity are explicitly defined. Probabilistic language models can be used to give a computationally explicit account of language complexity during comprehension. Whereas such models have so far predominantly been evaluated against behavioral data, only recently have the models been used to explain neurobiological signals. Measures obtained from these models emphasize the probabilistic, information-processing view of language understanding and provide a set of tools that can be used for testing neural hypotheses about language comprehension. Here, we provide a cursory review of the theoretical foundations and example neuroimaging studies employing probabilistic language models. We highlight the advantages and potential pitfalls of this approach and indicate avenues for future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. ORGANIZATIONAL AND METHODICAL BASES OF MULTICULTURAL SELF-ORGANIZATION OF STUDENTS IN THE ADDITIONAL FOREIGN LANGUAGE EDUCATION

    Directory of Open Access Journals (Sweden)

    V N Kartashova

    2016-12-01

    Full Text Available The article deals with the organizational and methodical bases of multicultural self-organization of the linguistic personality of the student in terms of additional foreign language education. According to the authors’ opinion, the methodological basis is a dialogue of cultures as a philosophy of mutual understanding, mutual relations in today’s global environment. Changing the socio-cultural context of foreign language education paradigm allows you to select multicultural (teaching a foreign language on the principle of “native culture - the culture of the foreign language speaking country - the culture of the world” and active (the development and functioning of a person in the normal course of his activities, where the starting point is the introduction of man to the world of culture and his self-development approach as a priority. The contents of additional education is oriented towards the disclosure and a possible solution of specific problems in the educational practice, and based on the principles of humanism and diversification.The article analyzes the individual programs of additional education and professional training in the field of foreign languages, developed by universities in recent decades. The authors present the experience of the scientific and methodological development and implementation at the department of foreign languages and teaching methods of Bunin Yelets State University of the additional foreign language education system that provides the multicultural self-organization of the student’s linguistic personality. The description of the program of professional retraining “The multicultural self-organization expert in the field of business, management and tourism (English”, designed for the students of non-language training areas, is presented, too. The positive dynamics of mastering foreign languages, the development of global attitude of the linguistic personality to the culture and his/her cultural

  19. Neural networks mediating sentence reading in the deaf

    Directory of Open Access Journals (Sweden)

    Elizabeth Ann Hirshorn

    2014-06-01

    Full Text Available The present work addresses the neural bases of sentence reading in deaf populations. To better understand the relative role of deafness and English knowledge in shaping the neural networks that mediate sentence reading, three populations with different degrees of English knowledge and depth of hearing loss were included – deaf signers, oral deaf and hearing individuals. The three groups were matched for reading comprehension and scanned while reading sentences. A similar neural network of left perisylvian areas was observed, supporting the view of a shared network of areas for reading despite differences in hearing and English knowledge. However, differences were observed, in particular in the auditory cortex, with deaf signers and oral deaf showing greatest bilateral superior temporal gyrus (STG recruitment as compared to hearing individuals. Importantly, within deaf individuals, the same STG area in the left hemisphere showed greater recruitment as hearing loss increased. To further understand the functional role of such auditory cortex re-organization after deafness, connectivity analyses were performed from the STG regions identified above. Connectivity from the left STG toward areas typically associated with semantic processing (BA45 and thalami was greater in deaf signers and in oral deaf as compared to hearing. In contrast, connectivity from left STG toward areas identified with speech-based processing was greater in hearing and in oral deaf as compared to deaf signers. These results support the growing literature indicating recruitment of auditory areas after congenital deafness for visually-mediated language functions, and establish that both auditory deprivation and language experience shape its functional reorganization. Implications for differential reliance on semantic vs. phonological pathways during reading in the three groups is discussed.

  20. A universal multilingual weightless neural network tagger via quantitative linguistics.

    Science.gov (United States)

    Carneiro, Hugo C C; Pedreira, Carlos E; França, Felipe M G; Lima, Priscila M V

    2017-07-01

    In the last decade, given the availability of corpora in several distinct languages, research on multilingual part-of-speech tagging started to grow. Amongst the novelties there is mWANN-Tagger (multilingual weightless artificial neural network tagger), a weightless neural part-of-speech tagger capable of being used for mostly-suffix-oriented languages. The tagger was subjected to corpora in eight languages of quite distinct natures and had a remarkable accuracy with very low sample deviation in every one of them, indicating the robustness of weightless neural systems for part-of-speech tagging tasks. However, mWANN-Tagger needed to be tuned for every new corpus, since each one required a different parameter configuration. For mWANN-Tagger to be truly multilingual, it should be usable for any new language with no need of parameter tuning. This article proposes a study that aims to find a relation between the lexical diversity of a language and the parameter configuration that would produce the best performing mWANN-Tagger instance. Preliminary analyses suggested that a single parameter configuration may be applied to the eight aforementioned languages. The mWANN-Tagger instance produced by this configuration was as accurate as the language-dependent ones obtained through tuning. Afterwards, the weightless neural tagger was further subjected to new corpora in languages that range from very isolating to polysynthetic ones. The best performing instances of mWANN-Tagger are again the ones produced by the universal parameter configuration. Hence, mWANN-Tagger can be applied to new corpora with no need of parameter tuning, making it a universal multilingual part-of-speech tagger. Further experiments with Universal Dependencies treebanks reveal that mWANN-Tagger may be extended and that it has potential to outperform most state-of-the-art part-of-speech taggers if better word representations are provided. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Does Handedness Affect the Cerebral Organization of Speech and Language in Individuals with Aphasia?

    Directory of Open Access Journals (Sweden)

    Juliana Baldo

    2014-04-01

    Although some earlier studies suggested distinct cerebral organizations for right- versus non-right-handed individuals, the neural correlates of fluency and comprehension were greatly overlapping between these groups in our sample of left hemisphere patients with aphasia.

  2. Language control in different contexts: the behavioural ecology of bilingual speakers

    Directory of Open Access Journals (Sweden)

    David William Green

    2011-05-01

    Full Text Available This paper proposes that different experimental contexts (single or dual language contexts permit different neural loci at which words in the target language can be selected. However, in order to develop a fuller understanding of the neural circuit mediating language control we need to consider the community context in which bilingual speakers typically use their two languages (the behavioural ecology of bilingual speakers. The contrast between speakers from code-switching and non-code switching communities offers a way to increase our understanding of the cortical, subcortical and, in particular, cerebellar structures involved in language control. It will also help us identify the non-verbal behavioural correlates associated with these control processes.

  3. Development of objective flow regime identification method using self-organizing neural network

    International Nuclear Information System (INIS)

    Lee, Jae Young; Kim, Nam Seok; Kwak, Nam Yee

    2004-01-01

    Two-phase flow shows various flow patterns according to the amount of the void and its relative velocity to the liquid flow. This variation directly affect the interfacial transfer which is the key factor for the design or analysis of the phase change systems. Especially the safety analysis of the nuclear power plant has been performed based on the numerical code furnished with the proper constitutive relations depending highly upon the flow regimes. Heavy efforts have been focused to identify the flow regime and at this moment we stand on relative very stable engineering background compare to the other research field. However, the issues related to objectiveness and transient flow regime are still open to study. Lee et al. and Ishii developed the method for the objective and instantaneous flow regime identification based on the neural network and new index of probability distribution of the flow regime which allows just one second observation for the flow regime identification. In the present paper, we developed the self-organized neural network for more objective approach to this problem. Kohonen's Self-Organizing Map (SOM) has been used for clustering, visualization, and abstraction. The SOM is trained through unsupervised competitive learning using a 'winner takes it all' policy. Therefore, its unsupervised training character delete the possible interference of the regime developer to the neural network training. After developing the computer code, we evaluate the performance of the code with the vertically upward two-phase flow in the pipes of 25.4 and 50.4 cmm I.D. Also, the sensitivity of the number of the clusters to the flow regime identification was made

  4. An Expedient Study on Back-Propagation (BPN) Neural Networks for Modeling Automated Evaluation of the Answers and Progress of Deaf Students' That Possess Basic Knowledge of the English Language and Computer Skills

    Science.gov (United States)

    Vrettaros, John; Vouros, George; Drigas, Athanasios S.

    This article studies the expediency of using neural networks technology and the development of back-propagation networks (BPN) models for modeling automated evaluation of the answers and progress of deaf students' that possess basic knowledge of the English language and computer skills, within a virtual e-learning environment. The performance of the developed neural models is evaluated with the correlation factor between the neural networks' response values and the real value data as well as the percentage measurement of the error between the neural networks' estimate values and the real value data during its training process and afterwards with unknown data that weren't used in the training process.

  5. Laser fluorimetry of mixtures of polyatomic organic compounds using artificial neural networks

    International Nuclear Information System (INIS)

    Dolenko, S A; Gerdova, I V; Dolenko, T A; Fadeev, V V

    2001-01-01

    New possibilities of laser fluorimetry offered by the use of algorithms for solving inverse problems based on artificial neural networks are demonstrated. A two-component mixture of polyatomic organic compounds is analysed by three methods of laser fluorimetry: a direct analysis of the fluorescence band, the kinetic fluorimetry (when durations of the laser pulse and the detector gate pulse are comparable with the fluorescence lifetimes or exceed them), and the saturation fluorimetry. The numerical experiments showed that the use of artificial neural networks in these methods provides a high practical stability of the solution of inverse problems and ensures a high sensitivity and a high accuracy of determining the contribution of components to fluorescence and of measuring molecular photophysical parameters, which can be used for the identification of components. (laser applications and other topics in quantum electronics)

  6. ERP correlates of German Sign Language processing in deaf native signers.

    Science.gov (United States)

    Hänel-Faulhaber, Barbara; Skotara, Nils; Kügow, Monique; Salden, Uta; Bottari, Davide; Röder, Brigitte

    2014-05-10

    The present study investigated the neural correlates of sign language processing of Deaf people who had learned German Sign Language (Deutsche Gebärdensprache, DGS) from their Deaf parents as their first language. Correct and incorrect signed sentences were presented sign by sign on a computer screen. At the end of each sentence the participants had to judge whether or not the sentence was an appropriate DGS sentence. Two types of violations were introduced: (1) semantically incorrect sentences containing a selectional restriction violation (implausible object); (2) morphosyntactically incorrect sentences containing a verb that was incorrectly inflected (i.e., incorrect direction of movement). Event-related brain potentials (ERPs) were recorded from 74 scalp electrodes. Semantic violations (implausible signs) elicited an N400 effect followed by a positivity. Sentences with a morphosyntactic violation (verb agreement violation) elicited a negativity followed by a broad centro-parietal positivity. ERP correlates of semantic and morphosyntactic aspects of DGS clearly differed from each other and showed a number of similarities with those observed in other signed and oral languages. These data suggest a similar functional organization of signed and oral languages despite the visual-spacial modality of sign language.

  7. Functional MRI language mapping in pre-surgical epilepsy patients ...

    African Journals Online (AJOL)

    Background. Functional magnetic resonance imaging (fMRI) is commonly applied to study the neural substrates of language in clinical research and for neurosurgical planning. fMRI language mapping is used to assess language lateralisation, or determine hemispheric dominance, and to localise regions of the brain ...

  8. Neural overlap of L1 and L2 semantic representations in speech: A decoding approach.

    Science.gov (United States)

    Van de Putte, Eowyn; De Baene, Wouter; Brass, Marcel; Duyck, Wouter

    2017-11-15

    Although research has now converged towards a consensus that both languages of a bilingual are represented in at least partly shared systems for language comprehension, it remains unclear whether both languages are represented in the same neural populations for production. We investigated the neural overlap between L1 and L2 semantic representations of translation equivalents using a production task in which the participants had to name pictures in L1 and L2. Using a decoding approach, we tested whether brain activity during the production of individual nouns in one language allowed predicting the production of the same concepts in the other language. Because both languages only share the underlying semantic representation (sensory and lexical overlap was maximally avoided), this would offer very strong evidence for neural overlap in semantic representations of bilinguals. Based on the brain activation for the individual concepts in one language in the bilateral occipito-temporal cortex and the inferior and the middle temporal gyrus, we could accurately predict the equivalent individual concepts in the other language. This indicates that these regions share semantic representations across L1 and L2 word production. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. RLL-1: A Representation Language Language

    Science.gov (United States)

    1980-10-01

    adaptable organisms over those which contain, built-in optimized features. Compare the extinct dinosaur , unable to adapt to new situations, with two of...natural language understandirq for KRL [Bobrow & Winograd] and OWL [Szolovits, et alD. For this reason , his language is ofL.:n inadequate for any...for no particular reason , switch the organ into its Oboe state. That is, the sequence which triggers a change to the organ is a Punction of the organ’s

  10. Fgf8-related secondary organizers exert different polarizing planar instructions along the mouse anterior neural tube.

    Science.gov (United States)

    Crespo-Enriquez, Ivan; Partanen, Juha; Martinez, Salvador; Echevarria, Diego

    2012-01-01

    Early brain patterning depends on proper arrangement of positional information. This information is given by gradients of secreted signaling molecules (morphogens) detected by individual cells within the responding tissue, leading to specific fate decisions. Here we report that the morphogen FGF8 exerts initially a differential signal activity along the E9.5 mouse neural tube. We demonstrate that this polarizing activity codes by RAS-regulated ERK1/2 signaling and depends on the topographical location of the secondary organizers: the isthmic organizer (IsO) and the anterior neural ridge (anr) but not on zona limitans intrathalamica (zli). Our results suggest that Sprouty2, a negative modulator of RAS/ERK pathway, is important for regulating Fgf8 morphogenetic signal activity by controlling Fgf8-induced signaling pathways and positional information during early brain development.

  11. Stone tools, language and the brain in human evolution

    Science.gov (United States)

    Stout, Dietrich; Chaminade, Thierry

    2012-01-01

    Long-standing speculations and more recent hypotheses propose a variety of possible evolutionary connections between language, gesture and tool use. These arguments have received important new support from neuroscientific research on praxis, observational action understanding and vocal language demonstrating substantial functional/anatomical overlap between these behaviours. However, valid reasons for scepticism remain as well as substantial differences in detail between alternative evolutionary hypotheses. Here, we review the current status of alternative ‘gestural’ and ‘technological’ hypotheses of language origins, drawing on current evidence of the neural bases of speech and tool use generally, and on recent studies of the neural correlates of Palaeolithic technology specifically. PMID:22106428

  12. Higher Language Ability is Related to Angular Gyrus Activation Increase During Semantic Processing, Independent of Sentence Incongruency

    Science.gov (United States)

    Van Ettinger-Veenstra, Helene; McAllister, Anita; Lundberg, Peter; Karlsson, Thomas; Engström, Maria

    2016-01-01

    This study investigates the relation between individual language ability and neural semantic processing abilities. Our aim was to explore whether high-level language ability would correlate to decreased activation in language-specific regions or rather increased activation in supporting language regions during processing of sentences. Moreover, we were interested if observed neural activation patterns are modulated by semantic incongruency similarly to previously observed changes upon syntactic congruency modulation. We investigated 27 healthy adults with a sentence reading task—which tapped language comprehension and inference, and modulated sentence congruency—employing functional magnetic resonance imaging (fMRI). We assessed the relation between neural activation, congruency modulation, and test performance on a high-level language ability assessment with multiple regression analysis. Our results showed increased activation in the left-hemispheric angular gyrus extending to the temporal lobe related to high language ability. This effect was independent of semantic congruency, and no significant relation between language ability and incongruency modulation was observed. Furthermore, there was a significant increase of activation in the inferior frontal gyrus (IFG) bilaterally when the sentences were incongruent, indicating that processing incongruent sentences was more demanding than processing congruent sentences and required increased activation in language regions. The correlation of high-level language ability with increased rather than decreased activation in the left angular gyrus, a region specific for language processing, is opposed to what the neural efficiency hypothesis would predict. We can conclude that no evidence is found for an interaction between semantic congruency related brain activation and high-level language performance, even though the semantic incongruent condition shows to be more demanding and evoking more neural activation. PMID

  13. Higher language ability is related to angular gyrus activation increase during semantic processing, independent of sentence incongruency

    Directory of Open Access Journals (Sweden)

    Helene eVan Ettinger-Veenstra

    2016-03-01

    Full Text Available This study investigates the relation between individual language ability and neural semantic processing abilities. Our aim was to explore whether high-level language ability would correlate to decreased activation in language-specific regions or rather increased activation in supporting language regions during processing of sentences. Moreover, we were interested if observed neural activation patterns are modulated by semantic incongruency similarly to previously observed changes upon syntactic congruency modulation. We investigated 27 healthy adults with a sentence reading task - which tapped language comprehension and inference, and modulated sentence congruency - employing functional magnetic resonance imaging. We assessed the relation between neural activation, congruency modulation, and test performance on a high-level language ability assessment with multiple regression analysis. Our results showed increased activation in the left-hemispheric angular gyrus extending to the temporal lobe related to high language ability. This effect was independent of semantic congruency, and no significant relation between language ability and incongruency modulation was observed. Furthermore, a significant increase of activation in the inferior frontal gyrus bilaterally when the sentences were incongruent, indicating that processing incongruent sentences was more demanding than processing congruent sentences and required increased activation in language regions. The correlation of high-level language ability with increased rather than decreased activation in the left angular gyrus, a region specific for language processing is opposed to what the neural efficiency hypothesis would predict. We can conclude that there is no evidence found for an interaction between semantic congruency related brain activation and high-level language performance, even though the semantic incongruent condition shows to be more demanding and evoking more neural activation.

  14. Noun and verb processing in aphasia: Behavioural profiles and neural correlates

    Directory of Open Access Journals (Sweden)

    Reem S.W. Alyahya

    Full Text Available The behavioural and neural processes underpinning different word classes, particularly nouns and verbs, have been a long-standing area of interest in psycholinguistic, neuropsychology and aphasiology research. This topic has theoretical implications concerning the organisation of the language system, as well as clinical consequences related to the management of patients with language deficits. Research findings, however, have diverged widely, which might, in part, reflect methodological differences, particularly related to controlling the psycholinguistic variations between nouns and verbs. The first aim of this study, therefore, was to develop a set of neuropsychological tests that assessed single-word production and comprehension with a matched set of nouns and verbs. Secondly, the behavioural profiles and neural correlates of noun and verb processing were explored, based on these novel tests, in a relatively large cohort of 48 patients with chronic post-stroke aphasia. A data-driven approach, principal component analysis (PCA, was also used to determine how noun and verb production and comprehension were related to the patients' underlying fundamental language domains. The results revealed no performance differences between noun and verb production and comprehension once matched on multiple psycholinguistic features including, most critically, imageability. Interestingly, the noun-verb differences found in previous studies were replicated in this study once un-matched materials were used. Lesion-symptom mapping revealed overlapping neural correlates of noun and verb processing along left temporal and parietal regions. These findings support the view that the neural representation of noun and verb processing at single-word level are jointly-supported by distributed cortical regions. The PCA generated five fundamental language and cognitive components of aphasia: phonological production, phonological recognition, semantics, fluency, and

  15. Transformation-invariant visual representations in self-organizing spiking neural networks.

    Science.gov (United States)

    Evans, Benjamin D; Stringer, Simon M

    2012-01-01

    The ventral visual pathway achieves object and face recognition by building transformation-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transformation-invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT) learning. However, it has not previously been investigated how transformation-invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP) where the change in synaptic strength is dependent on the relative times of the spikes emitted by the presynaptic and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF) neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model parameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

  16. Transform-invariant visual representations in self-organizing spiking neural networks

    Directory of Open Access Journals (Sweden)

    Benjamin eEvans

    2012-07-01

    Full Text Available The ventral visual pathway achieves object and face recognition by building transform-invariant representations from elementary visual features. In previous computer simulation studies with rate-coded neural networks, the development of transform invariant representations has been demonstrated using either of two biologically plausible learning mechanisms, Trace learning and Continuous Transformation (CT learning. However, it has not previously been investigated how transform invariant representations may be learned in a more biologically accurate spiking neural network. A key issue is how the synaptic connection strengths in such a spiking network might self-organize through Spike-Time Dependent Plasticity (STDP where the change in synaptic strength is dependent on the relative times of the spikes emitted by the pre- and postsynaptic neurons rather than simply correlated activity driving changes in synaptic efficacy. Here we present simulations with conductance-based integrate-and-fire (IF neurons using a STDP learning rule to address these gaps in our understanding. It is demonstrated that with the appropriate selection of model pa- rameters and training regime, the spiking network model can utilize either Trace-like or CT-like learning mechanisms to achieve transform-invariant representations.

  17. A Correlational Study of Graphic Organizers and Science Achievement of English Language Learners

    Science.gov (United States)

    Clarke, William Gordon

    English language learners (ELLs) demonstrate lower academic performance and have lower graduation and higher dropout rates than their non-ELL peers. The primary purpose of this correlational quantitative study was to investigate the relationship between the use of graphic organizer-infused science instruction and science learning of high school ELLs. Another objective was to determine if the method of instruction, socioeconomic status (SES), gender, and English language proficiency (ELP) were predictors of academic achievement of high school ELLs. Data were gathered from a New York City (NYC) high school fall 2012-2013 archival records of 145 ninth-grade ELLs who had received biology instruction in freestanding English as a second language (ESL) classes, followed by a test of their learning of the material. Fifty-four (37.2%) of these records were of students who had learned science by the conventional textbook method, and 91 (62.8%) by using graphic organizers. Data analysis employed the Statistical Package for the Social Sciences (SPSS) software for multiple regression analysis, which found graphic organizer use to be a significant predictor of New York State Regents Living Environment (NYSRLE) test scores (p < .01). One significant regression model was returned whereby, when combined, the four predictor variables (method of instruction, SES, gender, and ELP) explained 36% of the variance of the NYSRLE score. Implications of the study findings noted graphic organizer use as advantageous for ELL science achievement. Recommendations made for practice were for (a) the adoption of graphic organizer infused-instruction, (b) establishment of a protocol for the implementation of graphic organizer-infused instruction, and (c) increased length of graphic organizer instructional time. Recommendations made for future research were (a) a replication quantitative correlational study in two or more high schools, (b) a quantitative quasi-experimental quantitative study to

  18. Approaches for Language Identification in Mismatched Environments

    Science.gov (United States)

    2016-09-08

    domain adaptation, unsupervised learning , deep neural networks, bottleneck features 1. Introduction and task Spoken language identification (LID) is...the process of identifying the language in a spoken speech utterance. In recent years, great improvements in LID system performance have been seen...be the case in practice. Lastly, we conduct an out-of-set experiment where VoA data from 9 other languages (Amharic, Creole, Croatian, English

  19. Neural Tuning to Low-Level Features of Speech throughout the Perisylvian Cortex.

    Science.gov (United States)

    Berezutskaya, Julia; Freudenburg, Zachary V; Güçlü, Umut; van Gerven, Marcel A J; Ramsey, Nick F

    2017-08-16

    Despite a large body of research, we continue to lack a detailed account of how auditory processing of continuous speech unfolds in the human brain. Previous research showed the propagation of low-level acoustic features of speech from posterior superior temporal gyrus toward anterior superior temporal gyrus in the human brain (Hullett et al., 2016). In this study, we investigate what happens to these neural representations past the superior temporal gyrus and how they engage higher-level language processing areas such as inferior frontal gyrus. We used low-level sound features to model neural responses to speech outside of the primary auditory cortex. Two complementary imaging techniques were used with human participants (both males and females): electrocorticography (ECoG) and fMRI. Both imaging techniques showed tuning of the perisylvian cortex to low-level speech features. With ECoG, we found evidence of propagation of the temporal features of speech sounds along the ventral pathway of language processing in the brain toward inferior frontal gyrus. Increasingly coarse temporal features of speech spreading from posterior superior temporal cortex toward inferior frontal gyrus were associated with linguistic features such as voice onset time, duration of the formant transitions, and phoneme, syllable, and word boundaries. The present findings provide the groundwork for a comprehensive bottom-up account of speech comprehension in the human brain. SIGNIFICANCE STATEMENT We know that, during natural speech comprehension, a broad network of perisylvian cortical regions is involved in sound and language processing. Here, we investigated the tuning to low-level sound features within these regions using neural responses to a short feature film. We also looked at whether the tuning organization along these brain regions showed any parallel to the hierarchy of language structures in continuous speech. Our results show that low-level speech features propagate throughout the

  20. Prenatal Nicotine Exposure Disrupts Infant Neural Markers of Orienting.

    Science.gov (United States)

    King, Erin; Campbell, Alana; Belger, Aysenil; Grewen, Karen

    2017-08-17

    Prenatal nicotine exposure (PNE) from maternal cigarette-smoking is linked to developmental deficits, including impaired auditory processing, language, generalized intelligence, attention and sleep. Fetal brain undergoes massive growth, organization and connectivity during gestation, making it particularly vulnerable to neurotoxic insult. Nicotine binds to nicotinic acetylcholine receptors, which are extensively involved in growth, connectivity and function of developing neural circuitry and neurotransmitter systems. Thus, PNE may have long-term impact on neurobehavioral development. The purpose of this study was to compare the auditory K-complex, an event-related potential reflective of auditory gating, sleep preservation and memory consolidation during sleep, in infants with and without PNE and to relate these neural correlates to neurobehavioral development. We compared brain responses to an auditory paired-click paradigm in 3 to 5-month-old infants during Stage 2 sleep, when the K-complex is best observed. We measured component amplitude and delta activity during the K-complex. PNE may impair auditory sensory gating, which may contribute to disrupted sleep and to reduced auditory discrimination and learning, attention re-orienting and/or arousal during wakefulness reported in other studies. Links between PNE and reduced K-complex amplitude and delta power may represent altered cholinergic and GABAergic synaptic programming, and possibly reflect early neural bases for PNE-linked disruptions in sleep quality and auditory processing. These may pose significant disadvantage for language acquisition, attention, and social interaction necessary for academic and social success. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. Organization of anti-phase synchronization pattern in neural networks: what are the key factors?

    Directory of Open Access Journals (Sweden)

    Dong eLi

    2011-12-01

    Full Text Available Anti-phase oscillation has been widely observed in cortical neuralnetwork. Elucidating the mechanism underlying the organization ofanti-phase pattern is of significance for better understanding morecomplicated pattern formations in brain networks. In dynamicalsystems theory, the organization of anti-phase oscillation patternhas usually been considered to relate to time-delay in coupling.This is consistent to conduction delays in real neural networks inthe brain due to finite propagation velocity of action potentials.However, other structural factors in cortical neural network, suchas modular organization (connection density and the coupling types(excitatory or inhibitory, could also play an important role. Inthis work, we investigate the anti-phase oscillation patternorganized on a two-module network of either neuronal cell model orneural mass model, and analyze the impact of the conduction delaytimes, the connection densities, and coupling types. Our resultsshow that delay times and coupling types can play key roles in thisorganization. The connection densities may have an influence on thestability if an anti-phase pattern exists due to the other factors.Furthermore, we show that anti-phase synchronization of slowoscillations can be achieved with small delay times if there isinteraction between slow and fast oscillations. These results aresignificant for further understanding more realistic spatiotemporaldynamics of cortico-cortical communications.

  2. Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems.

    Science.gov (United States)

    Wang, Sheng-Jun; Ouyang, Guang; Guang, Jing; Zhang, Mingsha; Wong, K Y Michael; Zhou, Changsong

    2016-01-08

    Self-organized critical states (SOCs) and stochastic oscillations (SOs) are simultaneously observed in neural systems, which appears to be theoretically contradictory since SOCs are characterized by scale-free avalanche sizes but oscillations indicate typical scales. Here, we show that SOs can emerge in SOCs of small size systems due to temporal correlation between large avalanches at the finite-size cutoff, resulting from the accumulation-release process in SOCs. In contrast, the critical branching process without accumulation-release dynamics cannot exhibit oscillations. The reconciliation of SOCs and SOs is demonstrated both in the sandpile model and robustly in biologically plausible neuronal networks. The oscillations can be suppressed if external inputs eliminate the prominent slow accumulation process, providing a potential explanation of the widely studied Berger effect or event-related desynchronization in neural response. The features of neural oscillations and suppression are confirmed during task processing in monkey eye-movement experiments. Our results suggest that finite-size, columnar neural circuits may play an important role in generating neural oscillations around the critical states, potentially enabling functional advantages of both SOCs and oscillations for sensitive response to transient stimuli.

  3. Development of efficiency module of organization of Arctic sea cargo transportation with application of neural network technologies

    Science.gov (United States)

    Sobolevskaya, E. Yu; Glushkov, S. V.; Levchenko, N. G.; Orlov, A. P.

    2018-05-01

    The analysis of software intended for organizing and managing the processes of sea cargo transportation has been carried out. The shortcomings of information resources are presented, for the organization of work in the Arctic and Subarctic regions of the Far East: the lack of decision support systems, the lack of factor analysis to calculate the time and cost of delivery. The architecture of the module for calculating the effectiveness of the organization of sea cargo transportation has been developed. The simulation process has been considered, which is based on the neural network. The main classification factors with their weighting coefficients have been identified. The architecture of the neural network has been developed to calculate the efficiency of the organization of sea cargo transportation in Arctic conditions. The architecture of the intellectual system of organization of sea cargo transportation has been developed, taking into account the difficult navigation conditions in the Arctic. Its implementation will allow one to provide the management of the shipping company with predictive analytics; to support decision-making; to calculate the most efficient delivery route; to provide on demand online transportation forecast, to minimize the shipping cost, delays in transit, and risks to cargo safety.

  4. Strengthening Foreign Language Professional Organizations.

    Science.gov (United States)

    Dunham, Lowell

    1971-01-01

    The leitmotif of this address, inspired by lines found in William B. Yeats'"The Second Coming", underscores the need for a greater display of solidarity of language teachers through increased participation in professional associations. The work of the American Council on the Teaching of Foreign Languages (ACTFL) is discussed and noted to be vital…

  5. A Self-Organizing Incremental Neural Network based on local distribution learning.

    Science.gov (United States)

    Xing, Youlu; Shi, Xiaofeng; Shen, Furao; Zhou, Ke; Zhao, Jinxi

    2016-12-01

    In this paper, we propose an unsupervised incremental learning neural network based on local distribution learning, which is called Local Distribution Self-Organizing Incremental Neural Network (LD-SOINN). The LD-SOINN combines the advantages of incremental learning and matrix learning. It can automatically discover suitable nodes to fit the learning data in an incremental way without a priori knowledge such as the structure of the network. The nodes of the network store rich local information regarding the learning data. The adaptive vigilance parameter guarantees that LD-SOINN is able to add new nodes for new knowledge automatically and the number of nodes will not grow unlimitedly. While the learning process continues, nodes that are close to each other and have similar principal components are merged to obtain a concise local representation, which we call a relaxation data representation. A denoising process based on density is designed to reduce the influence of noise. Experiments show that the LD-SOINN performs well on both artificial and real-word data. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Cerebral organization of oral and signed language responses: case study evidence from amytal and cortical stimulation studies.

    Science.gov (United States)

    Mateer, C A; Rapport, R L; Kettrick, C

    1984-01-01

    A normally hearing left-handed patient familiar with American Sign Language (ASL) was assessed under sodium amytal conditions and with left cortical stimulation in both oral speech and signed English. Lateralization was mixed but complementary in each language mode: the right hemisphere perfusion severely disrupted motoric aspects of both types of language expression, the left hemisphere perfusion specifically disrupted features of grammatical and semantic usage in each mode of expression. Both semantic and syntactic aspects of oral and signed responses were altered during left posterior temporal-parietal stimulation. Findings are discussed in terms of the neurological organization of ASL and linguistic organization in cases of early left hemisphere damage.

  7. Prediction of the rejection of organic compounds (neutral and ionic) by nanofiltration and reverse osmosis membranes using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ammi, Yamina; Khaouane, Latifa; Hanini, Salah [University of Medea, Medea (Algeria)

    2015-11-15

    This work investigates the use of neural networks in modeling the rejection processes of organic compounds (neutral and ionic) by nanofiltration and reverse osmosis membranes. Three feed-forward neural network (NN) models, characterized by a similar structure (eleven neurons for NN1 and NN2 and twelve neurons for NN3 in the input layer, one hidden layer and one neuron in the output layer), are constructed with the aim of predicting the rejection of organic compounds (neutral and ionic). A set of 956 data points for NN1 and 701 data points for NN2 and NN3 were used to test the neural networks. 80%, 10%, and 10% of the total data were used, respectively, for the training, the validation, and the test of the three models. For the most promising neural network models, the predicted rejection values of the test dataset were compared to measured rejections values; good correlations were found (R= 0.9128 for NN1, R=0.9419 for NN2, and R=0.9527 for NN3). The root mean squared errors for the total dataset were 11.2430% for NN1, 9.0742% for NN2, and 8.2047% for NN3. Furthermore, the comparison between the predicted results and QSAR models shows that the neural network models gave far better.

  8. Prediction of the rejection of organic compounds (neutral and ionic) by nanofiltration and reverse osmosis membranes using neural networks

    International Nuclear Information System (INIS)

    Ammi, Yamina; Khaouane, Latifa; Hanini, Salah

    2015-01-01

    This work investigates the use of neural networks in modeling the rejection processes of organic compounds (neutral and ionic) by nanofiltration and reverse osmosis membranes. Three feed-forward neural network (NN) models, characterized by a similar structure (eleven neurons for NN1 and NN2 and twelve neurons for NN3 in the input layer, one hidden layer and one neuron in the output layer), are constructed with the aim of predicting the rejection of organic compounds (neutral and ionic). A set of 956 data points for NN1 and 701 data points for NN2 and NN3 were used to test the neural networks. 80%, 10%, and 10% of the total data were used, respectively, for the training, the validation, and the test of the three models. For the most promising neural network models, the predicted rejection values of the test dataset were compared to measured rejections values; good correlations were found (R= 0.9128 for NN1, R=0.9419 for NN2, and R=0.9527 for NN3). The root mean squared errors for the total dataset were 11.2430% for NN1, 9.0742% for NN2, and 8.2047% for NN3. Furthermore, the comparison between the predicted results and QSAR models shows that the neural network models gave far better.

  9. EDUCATIONAL PROGRAMMES OF BRITISH ORGANIZATIONS IN AZERBAIJAN AS AN ELEMENT OF THE UNITED KINGDOM FOREIGN LANGUAGE POLICY

    Directory of Open Access Journals (Sweden)

    G. Y. Niyazova

    2014-10-01

    Full Text Available The article considers the United Kingdom language policy on the territory of Azerbaijan after the Soviet Union collapse, which is a bright example of the world political map redrawing. Taking into account the fact that the language is an important tool of the extending one’s influence over the country, we can say with certainty that the success of the specific state laying a claim to play the leading role in on the global political arena strongly depends on its ability to promote its language abroad, to enhance its status and to create such conditions where in the foreign country its language conquers the status close to the status of the native language. In this regard, the United Kingdom activity can serve as an example of a successful foreign language state policy.The authors analyze the activity of such organizations as the British Council, the BBC and BP on spreading the English language. The aforesaid British organizations are the master plate of the efficient language state policy tools, as long as they not only actively develop the global picture of the world, but also promote the interests of the United Kingdom on the territory of the former Soviet Union.Azerbaijan encourages the United Kingdom intention to spread the English language on its territory and does its best in assisting in the implementation of the proposed initiatives, realizing that the spread of the English language being the language of a global communication in Azerbaijan would contribute to the raising of Azerbaijan status on the world arena.

  10. Getting the word out: Neural correlates of enthusiastic message propagation

    Directory of Open Access Journals (Sweden)

    Emily eFalk

    2012-11-01

    Full Text Available What happens in the mind of a person who first hears a potentially exciting idea? We examined the neural precursors of spreading ideas with enthusiasm, and dissect enthusiasm into component processes that can be identified through automated linguistic analysis, gestalt human ratings of combined linguistic and non-verbal cues, and points of convergence/divergence between the two. We combined tools from natural language processing with data gathered using fMRI, to link the neurocognitive mechanisms that are set in motion during initial exposure to ideas and subsequent behaviors of these message communicators outside of the scanner. Participants’ neural activity was recorded as they reviewed ideas for potential television show pilots. Participants’ language from video-taped interviews collected post-scan was transcribed and given to an automated linguistic sentiment analysis classifier, which returned ratings for evaluative language (evaluative vs. descriptive and valence (positive vs. negative. Separately, human coders rated the enthusiasm with which participants transmitted each idea. More positive sentiment ratings by the automated classifier were associated with activation in neural regions including medial prefrontal cortex; MPFC, precuneus/posterior cingulate cortex; PC/PCC, and medial temporal lobe; MTL. More evaluative, positive, descriptions were associated exclusively with neural activity in temporal parietal junction (TPJ. Finally, human ratings indicative of more enthusiastic sentiment were associated with activation across these regions (MPFC, PC/PCC, DMPFC, TPJ, MTL as well as in ventral striatum, inferior parietal lobule and premotor cortex. Taken together, these data demonstrate novel links between neural activity during initial idea encoding and the enthusiasm with which the ideas are subsequently delivered. These data also demonstrate the novel use of machine learning tools to link natural language data to neuroimaging data.

  11. Neural correlates of continuous causal word generation.

    Science.gov (United States)

    Wende, Kim C; Straube, Benjamin; Stratmann, Mirjam; Sommer, Jens; Kircher, Tilo; Nagels, Arne

    2012-09-01

    Causality provides a natural structure for organizing our experience and language. Causal reasoning during speech production is a distinct aspect of verbal communication, whose related brain processes are yet unknown. The aim of the current study was to investigate the neural mechanisms underlying the continuous generation of cause-and-effect coherences during overt word production. During fMRI data acquisition participants performed three verbal fluency tasks on identical cue words: A novel causal verbal fluency task (CVF), requiring the production of multiple reasons to a given cue word (e.g. reasons for heat are fire, sun etc.), a semantic (free association, FA, e.g. associations with heat are sweat, shower etc.) and a phonological control task (phonological verbal fluency, PVF, e.g. rhymes with heat are meat, wheat etc.). We found that, in contrast to PVF, both CVF and FA activated a left lateralized network encompassing inferior frontal, inferior parietal and angular regions, with further bilateral activation in middle and inferior as well as superior temporal gyri and the cerebellum. For CVF contrasted against FA, we found greater bold responses only in the left middle frontal cortex. Large overlaps in the neural activations during free association and causal verbal fluency indicate that the access to causal relationships between verbal concepts is at least partly based on the semantic neural network. The selective activation in the left middle frontal cortex for causal verbal fluency suggests that distinct neural processes related to cause-and-effect-relations are associated with the recruitment of middle frontal brain areas. Copyright © 2012 Elsevier Inc. All rights reserved.

  12. FOXP2 and the neuroanatomy of speech and language.

    Science.gov (United States)

    Vargha-Khadem, Faraneh; Gadian, David G; Copp, Andrew; Mishkin, Mortimer

    2005-02-01

    That speech and language are innate capacities of the human brain has long been widely accepted, but only recently has an entry point into the genetic basis of these remarkable faculties been found. The discovery of a mutation in FOXP2 in a family with a speech and language disorder has enabled neuroscientists to trace the neural expression of this gene during embryological development, track the effects of this gene mutation on brain structure and function, and so begin to decipher that part of our neural inheritance that culminates in articulate speech.

  13. Fully convolutional neural networks improve abdominal organ segmentation

    Science.gov (United States)

    Bobo, Meg F.; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J.; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G.; Hilmes, Melissa A.; Landman, Bennett A.

    2018-03-01

    Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities. 1

  14. Neural substrates of sublexical processing for spelling.

    Science.gov (United States)

    DeMarco, Andrew T; Wilson, Stephen M; Rising, Kindle; Rapcsak, Steven Z; Beeson, Pélagie M

    2017-01-01

    We used fMRI to examine the neural substrates of sublexical phoneme-grapheme conversion during spelling in a group of healthy young adults. Participants performed a writing-to-dictation task involving irregular words (e.g., choir), plausible nonwords (e.g., kroid), and a control task of drawing familiar geometric shapes (e.g., squares). Written production of both irregular words and nonwords engaged a left-hemisphere perisylvian network associated with reading/spelling and phonological processing skills. Effects of lexicality, manifested by increased activation during nonword relative to irregular word spelling, were noted in anterior perisylvian regions (posterior inferior frontal gyrus/operculum/precentral gyrus/insula), and in left ventral occipito-temporal cortex. In addition to enhanced neural responses within domain-specific components of the language network, the increased cognitive demands associated with spelling nonwords engaged domain-general frontoparietal cortical networks involved in selective attention and executive control. These results elucidate the neural substrates of sublexical processing during written language production and complement lesion-deficit correlation studies of phonological agraphia. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Language and Cognition Interaction Neural Mechanisms

    Science.gov (United States)

    2011-06-01

    resolution of processes in the brain, combined with magnetoencephalography (MEG), measurements of the magnetic field next to head , to provide a high...humans,” Anatomy and Embryology , vol. 210, no. 5-6, pp. 419– 421, 2005. [88] G. Rizzolatti and M. A. Arbib, “Language within our grasp,” Trends in

  16. Artificial neural networks applied to quantitative elemental analysis of organic material using PIXE

    International Nuclear Information System (INIS)

    Correa, R.; Chesta, M.A.; Morales, J.R.; Dinator, M.I.; Requena, I.; Vila, I.

    2006-01-01

    An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced emission) spectra of organic substances. Following the training stage ANN was applied to a subset of similar samples thus obtaining the elemental concentrations in muscle, liver and gills of Cyprinus carpio. Concentrations obtained with the ANN method are in full agreement with results from one standard analytical procedure, showing the high potentiality of ANN in PIXE quantitative analyses

  17. Artificial neural networks applied to quantitative elemental analysis of organic material using PIXE

    Energy Technology Data Exchange (ETDEWEB)

    Correa, R. [Universidad Tecnologica Metropolitana, Departamento de Fisica, Av. Jose Pedro Alessandri 1242, Nunoa, Santiago (Chile)]. E-mail: rcorrea@utem.cl; Chesta, M.A. [Universidad Nacional de Cordoba, Facultad de Matematica, Astronomia y Fisica, Medina Allende s/n Ciudad Universitaria, 5000 Cordoba (Argentina)]. E-mail: chesta@famaf.unc.edu.ar; Morales, J.R. [Universidad de Chile, Facultad de Ciencias, Departamento de Fisica, Las Palmeras 3425, Nunoa, Santiago (Chile)]. E-mail: rmorales@uchile.cl; Dinator, M.I. [Universidad de Chile, Facultad de Ciencias, Departamento de Fisica, Las Palmeras 3425, Nunoa, Santiago (Chile)]. E-mail: mdinator@uchile.cl; Requena, I. [Universidad de Granada, Departamento de Ciencias de la Computacion e Inteligencia Artificial, Daniel Saucedo Aranda s/n, 18071 Granada (Spain)]. E-mail: requena@decsai.ugr.es; Vila, I. [Universidad de Chile, Facultad de Ciencias, Departamento de Ecologia, Las Palmeras 3425, Nunoa, Santiago (Chile)]. E-mail: limnolog@uchile.cl

    2006-08-15

    An artificial neural network (ANN) has been trained with real-sample PIXE (particle X-ray induced emission) spectra of organic substances. Following the training stage ANN was applied to a subset of similar samples thus obtaining the elemental concentrations in muscle, liver and gills of Cyprinus carpio. Concentrations obtained with the ANN method are in full agreement with results from one standard analytical procedure, showing the high potentiality of ANN in PIXE quantitative analyses.

  18. Covalent growth factor tethering to direct neural stem cell differentiation and self-organization.

    Science.gov (United States)

    Ham, Trevor R; Farrag, Mahmoud; Leipzig, Nic D

    2017-04-15

    Tethered growth factors offer exciting new possibilities for guiding stem cell behavior. However, many of the current methods present substantial drawbacks which can limit their application and confound results. In this work, we developed a new method for the site-specific covalent immobilization of azide-tagged growth factors and investigated its utility in a model system for guiding neural stem cell (NSC) behavior. An engineered interferon-γ (IFN-γ) fusion protein was tagged with an N-terminal azide group, and immobilized to two different dibenzocyclooctyne-functionalized biomimetic polysaccharides (chitosan and hyaluronan). We successfully immobilized azide-tagged IFN-γ under a wide variety of reaction conditions, both in solution and to bulk hydrogels. To understand the interplay between surface chemistry and protein immobilization, we cultured primary rat NSCs on both materials and showed pronounced biological effects. Expectedly, immobilized IFN-γ increased neuronal differentiation on both materials. Expression of other lineage markers varied depending on the material, suggesting that the interplay of surface chemistry and protein immobilization plays a large role in nuanced cell behavior. We also investigated the bioactivity of immobilized IFN-γ in a 3D environment in vivo and found that it sparked the robust formation of neural tube-like structures from encapsulated NSCs. These findings support a wide range of potential uses for this approach and provide further evidence that adult NSCs are capable of self-organization when exposed to the proper microenvironment. For stem cells to be used effectively in regenerative medicine applications, they must be provided with the appropriate cues and microenvironment so that they integrate with existing tissue. This study explores a new method for guiding stem cell behavior: covalent growth factor tethering. We found that adding an N-terminal azide-tag to interferon-γ enabled stable and robust Cu-free 'click

  19. The small GTPase RhoA is required to maintain spinal cord neuroepithelium organization and the neural stem cell pool

    DEFF Research Database (Denmark)

    Herzog, Dominik; Loetscher, Pirmin; van Hengel, Jolanda

    2011-01-01

    ablation. We show that, in the spinal cord neuroepithelium, RhoA is essential to localize N-cadherin and ß-catenin to AJs and maintain apical-basal polarity of neural progenitor cells. Ablation of RhoA caused the loss of AJs and severe abnormalities in the organization of cells within the neuroepithelium......Dia1), does not localize to apical AJs in which it likely stabilizes intracellular adhesion by promoting local actin polymerization and microtubule organization. Furthermore, expressing a dominant-negative form of mDia1 in neural stem/progenitor cells results in a similar phenotype compared...... with that of the RhoA conditional knock-out, namely the loss of AJs and apical polarity. Together, our data show that RhoA signaling is necessary for AJ regulation and for the maintenance of mammalian neuroepithelium organization preventing precocious cell-cycle exit and differentiation....

  20. Early Childhood Stuttering and Electrophysiological Indices of Language Processing

    Science.gov (United States)

    Weber-Fox, Christine; Wray, Amanda Hampton; Arnold, Hayley

    2013-01-01

    We examined neural activity mediating semantic and syntactic processing in 27 preschool-age children who stutter (CWS) and 27 preschool-age children who do not stutter (CWNS) matched for age, nonverbal IQ and language abilities. All participants displayed language abilities and nonverbal IQ within the normal range. Event-related brain potentials (ERPs) were elicited while participants watched a cartoon video and heard naturally spoken sentences that were either correct or contained semantic or syntactic (phrase structure) violations. ERPs in CWS, compared to CWNS, were characterized by longer N400 peak latencies elicited by semantic processing. In the CWS, syntactic violations elicited greater negative amplitudes for the early time window (150–350 ms) over medial sites compared to CWNS. Additionally, the amplitude of the P600 elicited by syntactic violations relative to control words was significant over the left hemisphere for the CWNS but showed the reverse pattern in CWS, a robust effect only over the right hemisphere. Both groups of preschoolage children demonstrated marked and differential effects for neural processes elicited by semantic and phrase structure violations; however, a significant proportion of young CWS exhibit differences in the neural functions mediating language processing compared to CWNS despite normal language abilities. These results are the first to show that differences in event-related brain potentials reflecting language processing occur as early as the preschool years in CWS and provide the first evidence that atypical lateralization of hemispheric speech/language functions previously observed in the brains of adults who stutter begin to emerge near the onset of developmental stuttering. PMID:23773672

  1. Language, Perception, and the Schematic Representation of Spatial Relations

    Science.gov (United States)

    Amorapanth, Prin; Kranjec, Alexander; Bromberger, Bianca; Lehet, Matthew; Widick, Page; Woods, Adam J.; Kimberg, Daniel Y.; Chatterjee, Anjan

    2012-01-01

    Schemas are abstract nonverbal representations that parsimoniously depict spatial relations. Despite their ubiquitous use in maps and diagrams, little is known about their neural instantiation. We sought to determine the extent to which schematic representations are neurally distinguished from language on the one hand, and from rich perceptual…

  2. Distinct steps of neural induction revealed by Asterix, Obelix and TrkC, genes induced by different signals from the organizer.

    Directory of Open Access Journals (Sweden)

    Sonia Pinho

    2011-04-01

    Full Text Available The amniote organizer (Hensen's node can induce a complete nervous system when grafted into a peripheral region of a host embryo. Although BMP inhibition has been implicated in neural induction, non-neural cells cannot respond to BMP antagonists unless previously exposed to a node graft for at least 5 hours before BMP inhibitors. To define signals and responses during the first 5 hours of node signals, a differential screen was conducted. Here we describe three early response genes: two of them, Asterix and Obelix, encode previously undescribed proteins of unknown function but Obelix appears to be a nuclear RNA-binding protein. The third is TrkC, a neurotrophin receptor. All three genes are induced by a node graft within 4-5 hours but they differ in the extent to which they are inducible by FGF: FGF is both necessary and sufficient to induce Asterix, sufficient but not necessary to induce Obelix and neither sufficient nor necessary for induction of TrkC. These genes are also not induced by retinoic acid, Noggin, Chordin, Dkk1, Cerberus, HGF/SF, Somatostatin or ionomycin-mediated Calcium entry. Comparison of the expression and regulation of these genes with other early neural markers reveals three distinct "epochs", or temporal waves, of gene expression accompanying neural induction by a grafted organizer, which are mirrored by specific stages of normal neural plate development. The results are consistent with neural induction being a cascade of responses elicited by different signals, culminating in the formation of a patterned nervous system.

  3. Using Graphic Organizers as a Tool for the Development of Scientific Language

    Science.gov (United States)

    Mercuri, Sandra P.

    2010-01-01

    This observational study examines the effectiveness of graphic organizers two elementary teachers in California, United States use to teach the content and the academic language of science. The study was done during the 2006-2007 school year. The data was collected through field-notes and the audio recording of instructional activities, and they…

  4. International Conference on Artificial Neural Networks (ICANN)

    CERN Document Server

    Mladenov, Valeri; Kasabov, Nikola; Artificial Neural Networks : Methods and Applications in Bio-/Neuroinformatics

    2015-01-01

    The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new al...

  5. The evolution of language and thought.

    Science.gov (United States)

    Lieberman, Philip

    2016-06-20

    Language primarily evolved as a vocal medium that transmits the attributes of human culture and the necessities of daily communication. Human language has a long, complex evolutionary history. Language also serves as an instrument of thought since it has become evident that in the course of this process neural circuits that initially evolved to regulate motor control, motor responses to external events, and ultimately talking were recycled to serve tasks such as working memory, cognitive flexibility linguistic tasks such as comprehending distinctions in meaning conveyed by syntax. This precludes the human brain possessing an organ devoted exclusively to language, such as the Faculty of Language proposed by Chomsky (1972, 2012). In essence like Fodor's (1983) modular model, a restatement of archaic phrenological theories (Spurzheim, 1815). The subcortical basal ganglia can be traced back to early anurans. Although our knowledge of the neural circuits of the human brain is at a very early stage and incomplete, the findings of independent studies over the past 40 years, discussed here, have identified circuits linking the basal ganglia with various areas of prefrontal cortex, posterior cortical regions and other subcortical structures. These circuits are active in linguistic tasks such as lexical access, comprehending distinctions in meaning conferred by syntax and the range of higher cognitive tasks involving executive control and play a critical role in conferring cognitive flexibility. The cingulate cortex which appeared in Therapsids, transitional mammal-like reptiles who lived in age of the dinosaurs, most likely enhanced mother-infant interaction, contributing to success in the Darwinian (1859) "Struggle for Existence" - the survival of progeny. They continue to fill that role in present-day mammals as well as being involved in controlling laryngeal phonation during speech and directing attention (Newman & MacLean, 1983; Cummings, 1993". The cerebellum and

  6. Learning and adaptation: neural and behavioural mechanisms behind behaviour change

    Science.gov (United States)

    Lowe, Robert; Sandamirskaya, Yulia

    2018-01-01

    This special issue presents perspectives on learning and adaptation as they apply to a number of cognitive phenomena including pupil dilation in humans and attention in robots, natural language acquisition and production in embodied agents (robots), human-robot game play and social interaction, neural-dynamic modelling of active perception and neural-dynamic modelling of infant development in the Piagetian A-not-B task. The aim of the special issue, through its contributions, is to highlight some of the critical neural-dynamic and behavioural aspects of learning as it grounds adaptive responses in robotic- and neural-dynamic systems.

  7. Chinese Sentence Classification Based on Convolutional Neural Network

    Science.gov (United States)

    Gu, Chengwei; Wu, Ming; Zhang, Chuang

    2017-10-01

    Sentence classification is one of the significant issues in Natural Language Processing (NLP). Feature extraction is often regarded as the key point for natural language processing. Traditional ways based on machine learning can not take high level features into consideration, such as Naive Bayesian Model. The neural network for sentence classification can make use of contextual information to achieve greater results in sentence classification tasks. In this paper, we focus on classifying Chinese sentences. And the most important is that we post a novel architecture of Convolutional Neural Network (CNN) to apply on Chinese sentence classification. In particular, most of the previous methods often use softmax classifier for prediction, we embed a linear support vector machine to substitute softmax in the deep neural network model, minimizing a margin-based loss to get a better result. And we use tanh as an activation function, instead of ReLU. The CNN model improve the result of Chinese sentence classification tasks. Experimental results on the Chinese news title database validate the effectiveness of our model.

  8. Implementation of self-organizing neural networks for visuo-motor control of an industrial robot.

    Science.gov (United States)

    Walter, J A; Schulten, K I

    1993-01-01

    The implementation of two neural network algorithms for visuo-motor control of an industrial robot (Puma 562) is reported. The first algorithm uses a vector quantization technique, the ;neural-gas' network, together with an error correction scheme based on a Widrow-Hoff-type learning rule. The second algorithm employs an extended self-organizing feature map algorithm. Based on visual information provided by two cameras, the robot learns to position its end effector without an external teacher. Within only 3000 training steps, the robot-camera system is capable of reducing the positioning error of the robot's end effector to approximately 0.1% of the linear dimension of the work space. By employing adaptive feedback the robot succeeds in compensating not only slow calibration drifts, but also sudden changes in its geometry. Hardware aspects of the robot-camera system are discussed.

  9. How Language Is Embodied in Bilinguals and Children with Specific Language Impairment

    Science.gov (United States)

    Adams, Ashley M.

    2016-01-01

    This manuscript explores the role of embodied views of language comprehension and production in bilingualism and specific language impairment. Reconceptualizing popular models of bilingual language processing, the embodied theory is first extended to this area. Issues such as semantic grounding in a second language and potential differences between early and late acquisition of a second language are discussed. Predictions are made about how this theory informs novel ways of thinking about teaching a second language. Secondly, the comorbidity of speech, language, and motor impairments and how embodiment theory informs the discussion of the etiology of these impairments is examined. A hypothesis is presented suggesting that what is often referred to as specific language impairment may not be so specific due to widespread subclinical motor deficits in this population. Predictions are made about how weaknesses and instabilities in speech motor control, even at a subclinical level, may disrupt the neural network that connects acoustic input, articulatory motor plans, and semantics. Finally, I make predictions about how this information informs clinical practice for professionals such as speech language pathologists and occupational and physical therapists. These new hypotheses are placed within the larger framework of the body of work pertaining to semantic grounding, action-based language acquisition, and action-perception links that underlie language learning and conceptual grounding. PMID:27582716

  10. Distribution of language-related Cntnap2 protein in neural circuits critical for vocal learning.

    Science.gov (United States)

    Condro, Michael C; White, Stephanie A

    2014-01-01

    Variants of the contactin associated protein-like 2 (Cntnap2) gene are risk factors for language-related disorders including autism spectrum disorder, specific language impairment, and stuttering. Songbirds are useful models for study of human speech disorders due to their shared capacity for vocal learning, which relies on similar cortico-basal ganglia circuitry and genetic factors. Here we investigate Cntnap2 protein expression in the brain of the zebra finch, a songbird species in which males, but not females, learn their courtship songs. We hypothesize that Cntnap2 has overlapping functions in vocal learning species, and expect to find protein expression in song-related areas of the zebra finch brain. We further expect that the distribution of this membrane-bound protein may not completely mirror its mRNA distribution due to the distinct subcellular localization of the two molecular species. We find that Cntnap2 protein is enriched in several song control regions relative to surrounding tissues, particularly within the adult male, but not female, robust nucleus of the arcopallium (RA), a cortical song control region analogous to human layer 5 primary motor cortex. The onset of this sexually dimorphic expression coincides with the onset of sensorimotor learning in developing males. Enrichment in male RA appears due to expression in projection neurons within the nucleus, as well as to additional expression in nerve terminals of cortical projections to RA from the lateral magnocellular nucleus of the nidopallium. Cntnap2 protein expression in zebra finch brain supports the hypothesis that this molecule affects neural connectivity critical for vocal learning across taxonomic classes. Copyright © 2013 Wiley Periodicals, Inc.

  11. Comparison of fMRI on the cortical organization using two language tasks in normal subjects

    International Nuclear Information System (INIS)

    Jiang Zhen; Zhang Caiyuan; Cai Wu; Shen Junkang; Gong Zhigang

    2008-01-01

    Objective: To comparatively study the cortical organization using two different language tasks by BOLD-fMRI in normal subjects: Methods: BOLD-fMRI scan was performed in 8 healthy volunteers with right handiness during executing the two language tasks: picture-naming and word-generation. The AFNI software was used to analyze the functional data and to generate the statistical parametric maps for comparatively studying the activation areas of each task. Results: Both activation patterns for two language tasks shared a common brain network dispersed in frontal, parietal, and occipital lobe. The activation areas of occipital lobe for picture-naming was more obvious than those for word-generation. By contraries, the areas related to language processing for word-generation was more active than picture-imaging. Compared with picture naming, the activation patterns for word-generation was mainly left-lateralized. Conclusion: Both of two tasks can activate the brain network which dedicate to language processing, but each of them has its own characteristics according to the processing patterns. (authors)

  12. Neural electrical activity and neural network growth.

    Science.gov (United States)

    Gafarov, F M

    2018-05-01

    The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

  13. Self-Organizing Maps Neural Networks Applied to the Classification of Ethanol Samples According to the Region of Commercialization

    Directory of Open Access Journals (Sweden)

    Aline Regina Walkoff

    2017-10-01

    Full Text Available Physical-chemical analysis data were collected, from 998 ethanol samples of automotive ethanol commercialized in the northern, midwestern and eastern regions of the state of Paraná. The data presented self-organizing maps (SOM neural networks, which classified them according to those regions. The self-organizing maps best configuration had a 45 x 45 topology and 5000 training epochs, with a final learning rate of 6.7x10-4, a final neighborhood relationship of 3x10-2 and a mean quantization error of 2x10-2. This neural network provided a topological map depicting three separated groups, each one corresponding to samples of a same region of commercialization. Four maps of weights, one for each parameter, were presented. The network established the pH was the most important variable for classification and electrical conductivity the least one. The self-organizing maps application allowed the segmentation of alcohol samples, therefore identifying them according to the region of commercialization. DOI: http://dx.doi.org/10.17807/orbital.v9i4.982

  14. The neural correlates of agrammatism: Evidence from aphasic and healthy speakers performing an overt picture description task

    Directory of Open Access Journals (Sweden)

    Eva eSchoenberger

    2014-03-01

    Full Text Available Functional brain imaging studies have improved our knowledge of the neural localization of language functions and the functional recovery after a lesion. However, the neural correlates of agrammatic symptoms in aphasia remain largely unknown. The present fMRI study examined the neural correlates of morpho-syntactic encoding and agrammatic errors in continuous language production by combining three approaches. First, the neural mechanisms underlying natural morpho-syntactic processing in a picture description task were analyzed in 15 healthy speakers. Second, agrammatic-like speech behavior was induced in the same group of healthy speakers to study the underlying functional processes by limiting the utterance length. In a third approach, five agrammatic participants performed the picture description task to gain insights in the neural correlates of agrammatism and the functional reorganization of language processing after stroke. In all approaches, utterances were analyzed for syntactic completeness, complexity and morphology. Event-related data analysis was conducted by defining every clause-like unit (CLU as an event with its onset-time and duration. Agrammatic and correct CLUs were contrasted. Due to the small sample size as well as heterogeneous lesion sizes and sites with lesion foci in the insula lobe, inferior frontal, superior temporal and inferior parietal areas the activation patterns in the agrammatic speakers were analyzed on a single subject level. In the group of healthy speakers, posterior temporal and inferior parietal areas were associated with greater morpho-syntactic demands in complete and complex CLUs. The intentional manipulation of morpho-syntactic structures and the omission of function words were associated with additional inferior frontal activation. Overall, the results revealed that the investigation of the neural correlates of agrammatic language production can be reasonably conducted with an overt language production

  15. The neural correlates of agrammatism: Evidence from aphasic and healthy speakers performing an overt picture description task.

    Science.gov (United States)

    Schönberger, Eva; Heim, Stefan; Meffert, Elisabeth; Pieperhoff, Peter; da Costa Avelar, Patricia; Huber, Walter; Binkofski, Ferdinand; Grande, Marion

    2014-01-01

    Functional brain imaging studies have improved our knowledge of the neural localization of language functions and the functional reorganization after a lesion. However, the neural correlates of agrammatic symptoms in aphasia remain largely unknown. The present fMRI study examined the neural correlates of morpho-syntactic encoding and agrammatic errors in continuous language production by combining three approaches. First, the neural mechanisms underlying natural morpho-syntactic processing in a picture description task were analyzed in 15 healthy speakers. Second, agrammatic-like speech behavior was induced in the same group of healthy speakers to study the underlying functional processes by limiting the utterance length. In a third approach, five agrammatic participants performed the picture description task to gain insights in the neural correlates of agrammatism and the functional reorganization of language processing after stroke. In all approaches, utterances were analyzed for syntactic completeness, complexity, and morphology. Event-related data analysis was conducted by defining every clause-like unit (CLU) as an event with its onset-time and duration. Agrammatic and correct CLUs were contrasted. Due to the small sample size as well as heterogeneous lesion sizes and sites with lesion foci in the insula lobe, inferior frontal, superior temporal and inferior parietal areas the activation patterns in the agrammatic speakers were analyzed on a single subject level. In the group of healthy speakers, posterior temporal and inferior parietal areas were associated with greater morpho-syntactic demands in complete and complex CLUs. The intentional manipulation of morpho-syntactic structures and the omission of function words were associated with additional inferior frontal activation. Overall, the results revealed that the investigation of the neural correlates of agrammatic language production can be reasonably conducted with an overt language production paradigm.

  16. Multi-digit handwritten sindhi numerals recognition using som neural network

    International Nuclear Information System (INIS)

    Chandio, A.A.; Jalbani, A.H.; Awan, S.A.

    2017-01-01

    In this research paper a multi-digit Sindhi handwritten numerals recognition system using SOM Neural Network is presented. Handwritten digits recognition is one of the challenging tasks and a lot of research is being carried out since many years. A remarkable work has been done for recognition of isolated handwritten characters as well as digits in many languages like English, Arabic, Devanagari, Chinese, Urdu and Pashto. However, the literature reviewed does not show any remarkable work done for Sindhi numerals recognition. The recognition of Sindhi digits is a difficult task due to the various writing styles and different font sizes. Therefore, SOM (Self-Organizing Map), a NN (Neural Network) method is used which can recognize digits with various writing styles and different font sizes. Only one sample is required to train the network for each pair of multi-digit numerals. A database consisting of 4000 samples of multi-digits consisting only two digits from 10-50 and other matching numerals have been collected by 50 users and the experimental results of proposed method show that an accuracy of 86.89% is achieved. (author)

  17. Cortical Motor Organization, Mirror Neurons, and Embodied Language: An Evolutionary Perspective

    Directory of Open Access Journals (Sweden)

    Leonardo Fogassi

    2012-11-01

    Full Text Available The recent conceptual achievement that the cortical motor system plays a crucial role not only in motor control but also in higher cognitive functions has given a new perspective also on the involvement of motor cortex in language perception and production. In particular, there is evidence that the matching mechanism based on mirror neurons can be involved in both pho-nological recognition and retrieval of meaning, especially for action word categories, thus suggesting a contribution of an action–perception mechanism to the automatic comprehension of semantics. Furthermore, a compari-son of the anatomo-functional properties of the frontal motor cortex among different primates and their communicative modalities indicates that the combination of the voluntary control of the gestural communication systems and of the vocal apparatus has been the critical factor in the transition from a gestural-based communication into a predominantly speech-based system. Finally, considering that the monkey and human premotor-parietal motor system, plus the prefrontal cortex, are involved in the sequential motor organization of actions and in the hierarchical combination of motor elements, we propose that elements of such motor organization have been exploited in other domains, including some aspects of the syntactic structure of language.

  18. Bilingualism, dementia, cognitive and neural reserve.

    Science.gov (United States)

    Perani, Daniela; Abutalebi, Jubin

    2015-12-01

    We discuss the role of bilingualism as a source of cognitive reserve and we propose the putative neural mechanisms through which lifelong bilingualism leads to a neural reserve that delays the onset of dementia. Recent findings highlight that the use of more than one language affects the human brain in terms of anatomo-structural changes. It is noteworthy that recent evidence from different places and cultures throughout the world points to a significant delay of dementia onset in bilingual/multilingual individuals. This delay has been reported not only for Alzheimer's dementia and its prodromal mild cognitive impairment phase, but also for other dementias such as vascular and fronto-temporal dementia, and was found to be independent of literacy, education and immigrant status. Lifelong bilingualism represents a powerful cognitive reserve delaying the onset of dementia by approximately 4 years. As to the causal mechanism, because speaking more than one language heavily relies upon executive control and attention, brain systems handling these functions are more developed in bilinguals resulting in increases of gray and white matter densities that may help protect from dementia onset. These neurocognitive benefits are even more prominent when second language proficiency and exposure are kept high throughout life.

  19. Language and emotions: emotional Sapir-Whorf hypothesis.

    Science.gov (United States)

    Perlovsky, Leonid

    2009-01-01

    An emotional version of Sapir-Whorf hypothesis suggests that differences in language emotionalities influence differences among cultures no less than conceptual differences. Conceptual contents of languages and cultures to significant extent are determined by words and their semantic differences; these could be borrowed among languages and exchanged among cultures. Emotional differences, as suggested in the paper, are related to grammar and mostly cannot be borrowed. The paper considers conceptual and emotional mechanisms of language along with their role in the mind and cultural evolution. Language evolution from primordial undifferentiated animal cries is discussed: while conceptual contents increase, emotional reduced. Neural mechanisms of these processes are suggested as well as their mathematical models: the knowledge instinct, the dual model connecting language and cognition, neural modeling fields. Mathematical results are related to cognitive science, linguistics, and psychology. Experimental evidence and theoretical arguments are discussed. Dynamics of the hierarchy-heterarchy of human minds and cultures is formulated using mean-field approach and approximate equations are obtained. The knowledge instinct operating in the mind heterarchy leads to mechanisms of differentiation and synthesis determining ontological development and cultural evolution. These mathematical models identify three types of cultures: "conceptual" pragmatic cultures in which emotionality of language is reduced and differentiation overtakes synthesis resulting in fast evolution at the price of uncertainty of values, self doubts, and internal crises; "traditional-emotional" cultures where differentiation lags behind synthesis, resulting in cultural stability at the price of stagnation; and "multi-cultural" societies combining fast cultural evolution and stability. Unsolved problems and future theoretical and experimental directions are discussed.

  20. Cortical language activation in aphasia: a functional MRI study

    International Nuclear Information System (INIS)

    Xu Xiaojun; Zhang Minming; Shang Desheng; Wang Qidong; Luo Benyan

    2004-01-01

    Objective: To investigate the differences of the underlying neural basis of language processing between normal subjects and aphasics, and to study the feasibility for functional magnetic resonance imaging (fMRI) in examining the cortical language activation in clinical aphasics. Methods: fMRI was used to map language network in 6 normal subjects and 3 patients with aphasia who were in the stage of recovery from acute stroke. The participants performed word generation task during fMRI scanning, which measured the signal changes associated with regional neural activity induced by the task. These signal changes were processed to statistically generate the activation map that represented the language area. Results: In normal subjects, a distributed language network was activated. Activations were present in the frontal, temporal, parietal and occipital regions in normal group. In the patient group, however, no activation was showed in the left inferior frontal gyrus whether or not the patient had lesion in the left frontal lobe. Two patients showed activations in some right hemisphere regions where no activation appeared in normal subjects. Conclusion: The remote effect of focal lesion and functional redistribution or reorganization was found in aphasic patients. fMRI was useful in evaluating the language function in aphasic patients. (authors)

  1. Efficient organ localization using multi-label convolutional neural networks in thorax-abdomen CT scans

    Science.gov (United States)

    Efrain Humpire-Mamani, Gabriel; Arindra Adiyoso Setio, Arnaud; van Ginneken, Bram; Jacobs, Colin

    2018-04-01

    Automatic localization of organs and other structures in medical images is an important preprocessing step that can improve and speed up other algorithms such as organ segmentation, lesion detection, and registration. This work presents an efficient method for simultaneous localization of multiple structures in 3D thorax-abdomen CT scans. Our approach predicts the location of multiple structures using a single multi-label convolutional neural network for each orthogonal view. Each network takes extra slices around the current slice as input to provide extra context. A sigmoid layer is used to perform multi-label classification. The output of the three networks is subsequently combined to compute a 3D bounding box for each structure. We used our approach to locate 11 structures of interest. The neural network was trained and evaluated on a large set of 1884 thorax-abdomen CT scans from patients undergoing oncological workup. Reference bounding boxes were annotated by human observers. The performance of our method was evaluated by computing the wall distance to the reference bounding boxes. The bounding boxes annotated by the first human observer were used as the reference standard for the test set. Using the best configuration, we obtained an average wall distance of 3.20~+/-~7.33 mm in the test set. The second human observer achieved 1.23~+/-~3.39 mm. For all structures, the results were better than those reported in previously published studies. In conclusion, we proposed an efficient method for the accurate localization of multiple organs. Our method uses multiple slices as input to provide more context around the slice under analysis, and we have shown that this improves performance. This method can easily be adapted to handle more organs.

  2. Differences in Neural Correlates of Speech Perception in 3 Month Olds at High and Low Risk for Autism Spectrum Disorder.

    Science.gov (United States)

    Edwards, Laura A; Wagner, Jennifer B; Tager-Flusberg, Helen; Nelson, Charles A

    2017-10-01

    In this study, we investigated neural precursors of language acquisition as potential endophenotypes of autism spectrum disorder (ASD) in 3-month-old infants at high and low familial ASD risk. Infants were imaged using functional near-infrared spectroscopy while they listened to auditory stimuli containing syllable repetitions; their neural responses were analyzed over left and right temporal regions. While female low risk infants showed initial neural activation that decreased over exposure to repetition-based stimuli, potentially indicating a habituation response to repetition in speech, female high risk infants showed no changes in neural activity over exposure. This finding may indicate a potential neural endophenotype of language development or ASD specific to females at risk for the disorder.

  3. Neural implementation of musical expertise and cognitive transfers: Could they be promising in the framework of normal cognitive aging?

    Directory of Open Access Journals (Sweden)

    Baptiste eFAUVEL

    2013-10-01

    Full Text Available Brain plasticity allows the central nervous system of a given organism to cope with environmental demands. Therefore, the quality of mental processes relies partly on the interaction between the brain’s physiological maturation and individual daily experiences.In this review, we focus on the neural implementation of musical expertise at both an anatomical and a functional level. We then discuss how this neural implementation can explain transfers from musical learning to a broad range of nonmusical cognitive functions, including language, especially during child development. Finally, given that brain plasticity is still present in aging, we gather arguments to propose that musical practice could be a good environmental enrichment to promote cerebral and cognitive reserves, thereby reducing the deleterious effect of aging on cognitive functions.

  4. Neural Decoding of Bistable Sounds Reveals an Effect of Intention on Perceptual Organization.

    Science.gov (United States)

    Billig, Alexander J; Davis, Matthew H; Carlyon, Robert P

    2018-03-14

    Auditory signals arrive at the ear as a mixture that the brain must decompose into distinct sources based to a large extent on acoustic properties of the sounds. An important question concerns whether listeners have voluntary control over how many sources they perceive. This has been studied using pure high (H) and low (L) tones presented in the repeating pattern HLH-HLH-, which can form a bistable percept heard either as an integrated whole (HLH-) or as segregated into high (H-H-) and low (-L-) sequences. Although instructing listeners to try to integrate or segregate sounds affects reports of what they hear, this could reflect a response bias rather than a perceptual effect. We had human listeners (15 males, 12 females) continuously report their perception of such sequences and recorded neural activity using MEG. During neutral listening, a classifier trained on patterns of neural activity distinguished between periods of integrated and segregated perception. In other conditions, participants tried to influence their perception by allocating attention either to the whole sequence or to a subset of the sounds. They reported hearing the desired percept for a greater proportion of time than when listening neutrally. Critically, neural activity supported these reports; stimulus-locked brain responses in auditory cortex were more likely to resemble the signature of segregation when participants tried to hear segregation than when attempting to perceive integration. These results indicate that listeners can influence how many sound sources they perceive, as reflected in neural responses that track both the input and its perceptual organization. SIGNIFICANCE STATEMENT Can we consciously influence our perception of the external world? We address this question using sound sequences that can be heard either as coming from a single source or as two distinct auditory streams. Listeners reported spontaneous changes in their perception between these two interpretations while

  5. Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity

    Science.gov (United States)

    Moses, David A.; Mesgarani, Nima; Leonard, Matthew K.; Chang, Edward F.

    2016-10-01

    Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

  6. Application of a Shallow Neural Network to Short-Term Stock Trading

    OpenAIRE

    Madahar, Abhinav; Ma, Yuze; Patel, Kunal

    2017-01-01

    Machine learning is increasingly prevalent in stock market trading. Though neural networks have seen success in computer vision and natural language processing, they have not been as useful in stock market trading. To demonstrate the applicability of a neural network in stock trading, we made a single-layer neural network that recommends buying or selling shares of a stock by comparing the highest high of 10 consecutive days with that of the next 10 days, a process repeated for the stock's ye...

  7. Language Travel or Language Tourism: Have Educational Trips Changed So Much?

    Science.gov (United States)

    Laborda, Jesus Garcia

    2007-01-01

    This article points out the changes in organization, students and language learning that language trips, as contrasted with educational trips (of which language trips are a subgroup) have gone through in the last years. The article emphasizes the need to differentiate between language trips and language tourism based on issues of additional…

  8. Getting the word out: neural correlates of enthusiastic message propagation.

    Science.gov (United States)

    Falk, Emily B; O'Donnell, Matthew Brook; Lieberman, Matthew D

    2012-01-01

    What happens in the mind of a person who first hears a potentially exciting idea?We examined the neural precursors of spreading ideas with enthusiasm, and dissected enthusiasm into component processes that can be identified through automated linguistic analysis, gestalt human ratings of combined linguistic and non-verbal cues, and points of convergence/divergence between the two. We combined tools from natural language processing (NLP) with data gathered using fMRI to link the neurocognitive mechanisms that are set in motion during initial exposure to ideas and subsequent behaviors of these message communicators outside of the scanner. Participants' neural activity was recorded as they reviewed ideas for potential television show pilots. Participants' language from video-taped interviews collected post-scan was transcribed and given to an automated linguistic sentiment analysis (SA) classifier, which returned ratings for evaluative language (evaluative vs. descriptive) and valence (positive vs. negative). Separately, human coders rated the enthusiasm with which participants transmitted each idea. More positive sentiment ratings by the automated classifier were associated with activation in neural regions including medial prefrontal cortex; MPFC, precuneus/posterior cingulate cortex; PC/PCC, and medial temporal lobe; MTL. More evaluative, positive, descriptions were associated exclusively with neural activity in temporal-parietal junction (TPJ). Finally, human ratings indicative of more enthusiastic sentiment were associated with activation across these regions (MPFC, PC/PCC, DMPFC, TPJ, and MTL) as well as in ventral striatum (VS), inferior parietal lobule and premotor cortex. Taken together, these data demonstrate novel links between neural activity during initial idea encoding and the enthusiasm with which the ideas are subsequently delivered. This research lays the groundwork to use machine learning and neuroimaging data to study word of mouth communication and

  9. Getting the word out: neural correlates of enthusiastic message propagation

    Science.gov (United States)

    Falk, Emily B.; O'Donnell, Matthew Brook; Lieberman, Matthew D.

    2012-01-01

    What happens in the mind of a person who first hears a potentially exciting idea?We examined the neural precursors of spreading ideas with enthusiasm, and dissected enthusiasm into component processes that can be identified through automated linguistic analysis, gestalt human ratings of combined linguistic and non-verbal cues, and points of convergence/divergence between the two. We combined tools from natural language processing (NLP) with data gathered using fMRI to link the neurocognitive mechanisms that are set in motion during initial exposure to ideas and subsequent behaviors of these message communicators outside of the scanner. Participants' neural activity was recorded as they reviewed ideas for potential television show pilots. Participants' language from video-taped interviews collected post-scan was transcribed and given to an automated linguistic sentiment analysis (SA) classifier, which returned ratings for evaluative language (evaluative vs. descriptive) and valence (positive vs. negative). Separately, human coders rated the enthusiasm with which participants transmitted each idea. More positive sentiment ratings by the automated classifier were associated with activation in neural regions including medial prefrontal cortex; MPFC, precuneus/posterior cingulate cortex; PC/PCC, and medial temporal lobe; MTL. More evaluative, positive, descriptions were associated exclusively with neural activity in temporal-parietal junction (TPJ). Finally, human ratings indicative of more enthusiastic sentiment were associated with activation across these regions (MPFC, PC/PCC, DMPFC, TPJ, and MTL) as well as in ventral striatum (VS), inferior parietal lobule and premotor cortex. Taken together, these data demonstrate novel links between neural activity during initial idea encoding and the enthusiasm with which the ideas are subsequently delivered. This research lays the groundwork to use machine learning and neuroimaging data to study word of mouth communication and

  10. Individual language experience modulates rapid formation of cortical memory circuits for novel words

    Science.gov (United States)

    Kimppa, Lilli; Kujala, Teija; Shtyrov, Yury

    2016-01-01

    Mastering multiple languages is an increasingly important ability in the modern world; furthermore, multilingualism may affect human learning abilities. Here, we test how the brain’s capacity to rapidly form new representations for spoken words is affected by prior individual experience in non-native language acquisition. Formation of new word memory traces is reflected in a neurophysiological response increase during a short exposure to novel lexicon. Therefore, we recorded changes in electrophysiological responses to phonologically native and non-native novel word-forms during a perceptual learning session, in which novel stimuli were repetitively presented to healthy adults in either ignore or attend conditions. We found that larger number of previously acquired languages and earlier average age of acquisition (AoA) predicted greater response increase to novel non-native word-forms. This suggests that early and extensive language experience is associated with greater neural flexibility for acquiring novel words with unfamiliar phonology. Conversely, later AoA was associated with a stronger response increase for phonologically native novel word-forms, indicating better tuning of neural linguistic circuits to native phonology. The results suggest that individual language experience has a strong effect on the neural mechanisms of word learning, and that it interacts with the phonological familiarity of the novel lexicon. PMID:27444206

  11. Generalized regression neural network (GRNN)-based approach for colored dissolved organic matter (CDOM) retrieval: case study of Connecticut River at Middle Haddam Station, USA.

    Science.gov (United States)

    Heddam, Salim

    2014-11-01

    The prediction of colored dissolved organic matter (CDOM) using artificial neural network approaches has received little attention in the past few decades. In this study, colored dissolved organic matter (CDOM) was modeled using generalized regression neural network (GRNN) and multiple linear regression (MLR) models as a function of Water temperature (TE), pH, specific conductance (SC), and turbidity (TU). Evaluation of the prediction accuracy of the models is based on the root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (CC), and Willmott's index of agreement (d). The results indicated that GRNN can be applied successfully for prediction of colored dissolved organic matter (CDOM).

  12. Measuring language lateralisation with different language tasks: a systematic review

    Directory of Open Access Journals (Sweden)

    Abigail R. Bradshaw

    2017-10-01

    Full Text Available Language lateralisation refers to the phenomenon in which one hemisphere (typically the left shows greater involvement in language functions than the other. Measurement of laterality is of interest both to researchers investigating the neural organisation of the language system and to clinicians needing to establish an individual’s hemispheric dominance for language prior to surgery, as in patients with intractable epilepsy. Recently, there has been increasing awareness of the possibility that different language processes may develop hemispheric lateralisation independently, and to varying degrees. However, it is not always clear whether differences in laterality across language tasks with fMRI are reflective of meaningful variation in hemispheric lateralisation, or simply of trivial methodological differences between paradigms. This systematic review aims to assess different language tasks in terms of the strength, reliability and robustness of the laterality measurements they yield with fMRI, to look at variability that is both dependent and independent of aspects of study design, such as the baseline task, region of interest, and modality of the stimuli. Recommendations are made that can be used to guide task design; however, this review predominantly highlights that the current high level of methodological variability in language paradigms prevents conclusions as to how different language functions may lateralise independently. We conclude with suggestions for future research using tasks that engage distinct aspects of language functioning, whilst being closely matched on non-linguistic aspects of task design (e.g., stimuli, task timings etc; such research could produce more reliable and conclusive insights into language lateralisation. This systematic review was registered as a protocol on Open Science Framework: https://osf.io/5vmpt/.

  13. Drosophila olfactory memory: single genes to complex neural circuits.

    Science.gov (United States)

    Keene, Alex C; Waddell, Scott

    2007-05-01

    A central goal of neuroscience is to understand how neural circuits encode memory and guide behaviour. Studying simple, genetically tractable organisms, such as Drosophila melanogaster, can illuminate principles of neural circuit organization and function. Early genetic dissection of D. melanogaster olfactory memory focused on individual genes and molecules. These molecular tags subsequently revealed key neural circuits for memory. Recent advances in genetic technology have allowed us to manipulate and observe activity in these circuits, and even individual neurons, in live animals. The studies have transformed D. melanogaster from a useful organism for gene discovery to an ideal model to understand neural circuit function in memory.

  14. Self: an adaptive pressure arising from self-organization, chaotic dynamics, and neural Darwinism.

    Science.gov (United States)

    Bruzzo, Angela Alessia; Vimal, Ram Lakhan Pandey

    2007-12-01

    In this article, we establish a model to delineate the emergence of "self" in the brain making recourse to the theory of chaos. Self is considered as the subjective experience of a subject. As essential ingredients of subjective experiences, our model includes wakefulness, re-entry, attention, memory, and proto-experiences. The stability as stated by chaos theory can potentially describe the non-linear function of "self" as sensitive to initial conditions and can characterize it as underlying order from apparently random signals. Self-similarity is discussed as a latent menace of a pathological confusion between "self" and "others". Our test hypothesis is that (1) consciousness might have emerged and evolved from a primordial potential or proto-experience in matter, such as the physical attractions and repulsions experienced by electrons, and (2) "self" arises from chaotic dynamics, self-organization and selective mechanisms during ontogenesis, while emerging post-ontogenically as an adaptive pressure driven by both volume and synaptic-neural transmission and influencing the functional connectivity of neural nets (structure).

  15. Intra-cranial recordings of brain activity during language production

    Directory of Open Access Journals (Sweden)

    Anais eLlorens

    2011-12-01

    Full Text Available Recent findings in the neurophysiology of language production have provided a detailed description of the brain network underlying this behavior, as well as some indications about the timing of operations. Despite their invaluable utility, these data generally suffer from limitations either in terms of temporal resolution, or in terms of spatial localization. In addition, studying the neural basis of speech is complicated by the presence of articulation artifacts such as electro-myographic activity that interferes with the neural signal. These difficulties are virtually absent in a powerful albeit much less frequent methodology, namely the recording of intra-cranial brain activity (iEEG. Such recordings are only possible under very specific clinical circumstances requiring functional mapping before brain surgery, most notably patients that suffer for pharmaco-resistant epilepsy. Here we review the research conducted with this methodology in the field of language production, with explicit consideration of its advantages and drawbacks. The available evidence is shown to be diverse, both in terms of the tasks and cognitive processes tested and in terms of the brain localizations being studied. Still, the review provides valuable information for characterizing the dynamics of the neural events occurring in the language production network. Following modality specific activities (in auditory or visual cortices, there is a convergence of activity in superior temporal sulcus, which is a plausible neural correlate of phonological encoding processes. Later, between 500 and 800 ms, inferior frontal gyrus (around Broca's area is involved. Peri-rolandic areas are recruited in the two modalities relatively early (200-500 ms window, suggesting a very early involvement of (pre- motor processes. We discuss how some of these findings may be at odds with conclusions drawn from available meta-analysis of language production.

  16. Neural correlates of audiovisual speech processing in a second language.

    Science.gov (United States)

    Barrós-Loscertales, Alfonso; Ventura-Campos, Noelia; Visser, Maya; Alsius, Agnès; Pallier, Christophe; Avila Rivera, César; Soto-Faraco, Salvador

    2013-09-01

    Neuroimaging studies of audiovisual speech processing have exclusively addressed listeners' native language (L1). Yet, several behavioural studies now show that AV processing plays an important role in non-native (L2) speech perception. The current fMRI study measured brain activity during auditory, visual, audiovisual congruent and audiovisual incongruent utterances in L1 and L2. BOLD responses to congruent AV speech in the pSTS were stronger than in either unimodal condition in both L1 and L2. Yet no differences in AV processing were expressed according to the language background in this area. Instead, the regions in the bilateral occipital lobe had a stronger congruency effect on the BOLD response (congruent higher than incongruent) in L2 as compared to L1. According to these results, language background differences are predominantly expressed in these unimodal regions, whereas the pSTS is similarly involved in AV integration regardless of language dominance. Copyright © 2013 Elsevier Inc. All rights reserved.

  17. The Recruitment Theory of Language Origins

    Science.gov (United States)

    Steels, Luc

    Tremendous progress has been made recently on the fascinating question of the origins and evolution of language (see e.g. (55), (7), (9), (31)). There is no widely accepted complete theory yet, but several proposals are on the table and observations and experiments are proceeding. This chapter focuses on the recruitment theory of language origins which we have been exploring for almost ten years now. This theory argues that language users recruit and try out different strategies for solving the task of communication and retain those that maximise communicative success and cognitive economy. Each strategy requires specific cognitive neural mechanisms, which in themselves serve a wide range of purposes and therefore may have evolved or could be learned independently of language.

  18. Modular representation of layered neural networks.

    Science.gov (United States)

    Watanabe, Chihiro; Hiramatsu, Kaoru; Kashino, Kunio

    2018-01-01

    Layered neural networks have greatly improved the performance of various applications including image processing, speech recognition, natural language processing, and bioinformatics. However, it is still difficult to discover or interpret knowledge from the inference provided by a layered neural network, since its internal representation has many nonlinear and complex parameters embedded in hierarchical layers. Therefore, it becomes important to establish a new methodology by which layered neural networks can be understood. In this paper, we propose a new method for extracting a global and simplified structure from a layered neural network. Based on network analysis, the proposed method detects communities or clusters of units with similar connection patterns. We show its effectiveness by applying it to three use cases. (1) Network decomposition: it can decompose a trained neural network into multiple small independent networks thus dividing the problem and reducing the computation time. (2) Training assessment: the appropriateness of a trained result with a given hyperparameter or randomly chosen initial parameters can be evaluated by using a modularity index. And (3) data analysis: in practical data it reveals the community structure in the input, hidden, and output layers, which serves as a clue for discovering knowledge from a trained neural network. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Forecasting the mortality rates of Indonesian population by using neural network

    Science.gov (United States)

    Safitri, Lutfiani; Mardiyati, Sri; Rahim, Hendrisman

    2018-03-01

    A model that can represent a problem is required in conducting a forecasting. One of the models that has been acknowledged by the actuary community in forecasting mortality rate is the Lee-Certer model. Lee Carter model supported by Neural Network will be used to calculate mortality forecasting in Indonesia. The type of Neural Network used is feedforward neural network aligned with backpropagation algorithm in python programming language. And the final result of this study is mortality rate in forecasting Indonesia for the next few years

  20. Exploring the Neural Substrates of Phonological Recovery for Symposium: Neural Correlates of Recovery and Rehabilitation

    Directory of Open Access Journals (Sweden)

    Pelagie M Beeson

    2015-10-01

    All participants improved written language abilities in response to treatment, but one subgroup was limited in their ability to regain phonological skills. Both anterior and posterior components of the perisylvian phonological network were damaged in that group. These findings are consistent with fMRI activation when healthy adults write nonwords, and provide insight regarding neural support necessary for phonological rehabilitation.

  1. Cerebellar language mapping and cerebral language dominance in pediatric epilepsy surgery patients

    Directory of Open Access Journals (Sweden)

    Jennifer N. Gelinas, MD, PhD

    2014-01-01

    Conclusions: Cerebellar language activation occurs in homologous regions of Crus I/II contralateral to cerebral language activation in patients with both right and left cerebral language dominance. Cerebellar language laterality could contribute to comprehensive pre-operative evaluation of language lateralization in pediatric epilepsy surgery patients. Our data suggest that patients with atypical cerebellar language activation are at risk for having atypical cerebral language organization.

  2. Self-organizing neural networks for automatic detection and classification of contrast-enhancing lesions in dynamic MR-mammography

    International Nuclear Information System (INIS)

    Vomweg, T.W.; Teifke, A.; Kauczor, H.U.; Achenbach, T.; Rieker, O.; Schreiber, W.G.; Heitmann, K.R.; Beier, T.; Thelen, M.

    2005-01-01

    Purpose: Investigation and statistical evaluation of 'Self-Organizing Maps', a special type of neural networks in the field of artificial intelligence, classifying contrast enhancing lesions in dynamic MR-mammography. Material and Methods: 176 investigations with proven histology after core biopsy or operation were randomly divided into two groups. Several Self-Organizing Maps were trained by investigations of the first group to detect and classify contrast enhancing lesions in dynamic MR-mammography. Each single pixel's signal/time curve of all patients within the second group was analyzed by the Self-Organizing Maps. The likelihood of malignancy was visualized by color overlays on the MR-images. At last assessment of contrast-enhancing lesions by each different network was rated visually and evaluated statistically. Results: A well balanced neural network achieved a sensitivity of 90.5% and a specificity of 72.2% in predicting malignancy of 88 enhancing lesions. Detailed analysis of false-positive results revealed that every second fibroadenoma showed a 'typical malignant' signal/time curve without any chance to differentiate between fibroadenomas and malignant tissue regarding contrast enhancement alone; but this special group of lesions was represented by a well-defined area of the Self-Organizing Map. Discussion: Self-Organizing Maps are capable of classifying a dynamic signal/time curve as 'typical benign' or 'typical malignant'. Therefore, they can be used as second opinion. In view of the now known localization of fibroadenomas enhancing like malignant tumors at the Self-Organizing Map, these lesions could be passed to further analysis by additional post-processing elements (e.g., based on T2-weighted series or morphology analysis) in the future. (orig.)

  3. Neural Control of Rising and Falling Tones in Mandarin Speakers Who Stutter

    Science.gov (United States)

    Howell, Peter; Jiang, Jing; Peng, Danling; Lu, Chunming

    2012-01-01

    Neural control of rising and falling tones in Mandarin people who stutter (PWS) was examined by comparing with that which occurs in fluent speakers [Howell, Jiang, Peng, and Lu (2012). Neural control of fundamental frequency rise and fall in Mandarin tones. "Brain and Language, 121"(1), 35-46]. Nine PWS and nine controls were scanned. Functional…

  4. Principles of neural information processing

    CERN Document Server

    Seelen, Werner v

    2016-01-01

    In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing as well as recent and authoritative research. The books´ guiding principles are the main purpose of neural activity, namely, to organize behavior to ensure survival, as well as the understanding of the evolutionary genesis of the brain. Among the developed principles and strategies belong self-organization of neural systems, flexibility, the active interpretation of the world by means of construction and prediction as well as their embedding into the world, all of which form the framework of the presented description. Since, in brains, their partial self-organization, the lifelong adaptation and their use of various methods of processing incoming information are all interconnected, the authors have chosen not only neurobiology and evolution theory as a basis for the elaboration of such a framework, but also syst...

  5. Neural changes underlying early stages of L2 vocabulary acquisition.

    Science.gov (United States)

    Pu, He; Holcomb, Phillip J; Midgley, Katherine J

    2016-11-01

    Research has shown neural changes following second language (L2) acquisition after weeks or months of instruction. But are such changes detectable even earlier than previously shown? The present study examines the electrophysiological changes underlying the earliest stages of second language vocabulary acquisition by recording event-related potentials (ERPs) within the first week of learning. Adult native English speakers with no previous Spanish experience completed less than four hours of Spanish vocabulary training, with pre- and post-training ERPs recorded to a backward translation task. Results indicate that beginning L2 learners show rapid neural changes following learning, manifested in changes to the N400 - an ERP component sensitive to lexicosemantic processing and degree of L2 proficiency. Specifically, learners in early stages of L2 acquisition show growth in N400 amplitude to L2 words following learning as well as a backward translation N400 priming effect that was absent pre-training. These results were shown within days of minimal L2 training, suggesting that the neural changes captured during adult second language acquisition are more rapid than previously shown. Such findings are consistent with models of early stages of bilingualism in adult learners of L2 ( e.g. Kroll and Stewart's RHM) and reinforce the use of ERP measures to assess L2 learning.

  6. The role of reward in word learning and its implications for language acquisition.

    Science.gov (United States)

    Ripollés, Pablo; Marco-Pallarés, Josep; Hielscher, Ulrike; Mestres-Missé, Anna; Tempelmann, Claus; Heinze, Hans-Jochen; Rodríguez-Fornells, Antoni; Noesselt, Toemme

    2014-11-03

    The exact neural processes behind humans' drive to acquire a new language--first as infants and later as second-language learners--are yet to be established. Recent theoretical models have proposed that during human evolution, emerging language-learning mechanisms might have been glued to phylogenetically older subcortical reward systems, reinforcing human motivation to learn a new language. Supporting this hypothesis, our results showed that adult participants exhibited robust fMRI activation in the ventral striatum (VS)--a core region of reward processing--when successfully learning the meaning of new words. This activation was similar to the VS recruitment elicited using an independent reward task. Moreover, the VS showed enhanced functional and structural connectivity with neocortical language areas during successful word learning. Together, our results provide evidence for the neural substrate of reward and motivation during word learning. We suggest that this strong functional and anatomical coupling between neocortical language regions and the subcortical reward system provided a crucial advantage in humans that eventually enabled our lineage to successfully acquire linguistic skills. Copyright © 2014 Elsevier Ltd. All rights reserved.

  7. Natural Language Processing with Small Feed-Forward Networks

    OpenAIRE

    Botha, Jan A.; Pitler, Emily; Ma, Ji; Bakalov, Anton; Salcianu, Alex; Weiss, David; McDonald, Ryan; Petrov, Slav

    2017-01-01

    We show that small and shallow feed-forward neural networks can achieve near state-of-the-art results on a range of unstructured and structured language processing tasks while being considerably cheaper in memory and computational requirements than deep recurrent models. Motivated by resource-constrained environments like mobile phones, we showcase simple techniques for obtaining such small neural network models, and investigate different tradeoffs when deciding how to allocate a small memory...

  8. Neural overlap of L1 and L2 semantic representations across visual and auditory modalities : A decoding approach

    NARCIS (Netherlands)

    Van De Putte, Eowyn; De Baene, W.; Price, Cathy J; Duyck, Wouter

    2018-01-01

    This study investigated whether brain activity in Dutch-French bilinguals during semantic access to concepts from one language could be used to predict neural activation during access to the same concepts from another language, in different language modalities/tasks. This was tested using

  9. Long-Term Experience with Chinese Language Shapes the Fusiform Asymmetry of English Reading

    Science.gov (United States)

    Mei, Leilei; Xue, Gui; Lu, Zhong-Lin; Chen, Chuansheng; Wei, Miao; He, Qinghua; Dong, Qi

    2015-01-01

    Previous studies have suggested differential engagement of the bilateral fusiform gyrus in the processing of Chinese and English. The present study tested the possibility that long-term experience with Chinese language affects the fusiform laterality of English reading by comparing three samples: Chinese speakers, English speakers with Chinese experience, and English speakers without Chinese experience. We found that, when reading words in their respective native language, Chinese and English speakers without Chinese experience differed in functional laterality of the posterior fusiform region (right laterality for Chinese speakers, but left laterality for English speakers). More importantly, compared with English speakers without Chinese experience, English speakers with Chinese experience showed more recruitment of the right posterior fusiform cortex for English words and pseudowords, which is similar to how Chinese speakers processed Chinese. These results suggest that long-term experience with Chinese shapes the fusiform laterality of English reading and have important implications for our understanding of the cross-language influences in terms of neural organization and of the functions of different fusiform subregions in reading. PMID:25598049

  10. Dynamic spatial organization of the occipito-temporal word form area for second language processing.

    Science.gov (United States)

    Gao, Yue; Sun, Yafeng; Lu, Chunming; Ding, Guosheng; Guo, Taomei; Malins, Jeffrey G; Booth, James R; Peng, Danling; Liu, Li

    2017-08-01

    Despite the left occipito-temporal region having shown consistent activation in visual word form processing across numerous studies in different languages, the mechanisms by which word forms of second languages are processed in this region remain unclear. To examine this more closely, 16 Chinese-English and 14 English-Chinese late bilinguals were recruited to perform lexical decision tasks to visually presented words in both their native and second languages (L1 and L2) during functional magnetic resonance imaging scanning. Here we demonstrate that visual word form processing for L1 versus L2 engaged different spatial areas of the left occipito-temporal region. Namely, the spatial organization of the visual word form processing in the left occipito-temporal region is more medial and posterior for L2 than L1 processing in Chinese-English bilinguals, whereas activation is more lateral and anterior for L2 in English-Chinese bilinguals. In addition, for Chinese-English bilinguals, more lateral recruitment of the occipito-temporal region was correlated with higher L2 proficiency, suggesting higher L2 proficiency is associated with greater involvement of L1-preferred mechanisms. For English-Chinese bilinguals, higher L2 proficiency was correlated with more lateral and anterior activation of the occipito-temporal region, suggesting higher L2 proficiency is associated with greater involvement of L2-preferred mechanisms. Taken together, our results indicate that L1 and L2 recruit spatially different areas of the occipito-temporal region in visual word processing when the two scripts belong to different writing systems, and that the spatial organization of this region for L2 visual word processing is dynamically modulated by L2 proficiency. Specifically, proficiency in L2 in Chinese-English is associated with assimilation to the native language mechanisms, whereas L2 in English-Chinese is associated with accommodation to second language mechanisms. Copyright © 2017

  11. Le Rapport langue-culture dans les organisations internationales: Pour Une Sociologie des organisations internationales (The Relationship between Language and Culture in International Organizations: Toward a Sociology of International Organizations).

    Science.gov (United States)

    Jastrab de Saint Robert, de Marie-Josee

    1988-01-01

    Understanding the work of international organizations requires an understanding of the relationship between language and culture, a relationship evident in the activities of the international organizations. This relationship is partly responsible for the negative image of such organizations. Research in the sociology of international organizations…

  12. 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.

  13. Cerebral and cerebellar language organization in a right-handed subject with a left temporal porencephalic cyst : An fMRI study

    NARCIS (Netherlands)

    De Coninck, Mattias; Van Hecke, Wim; Crols, Roe; van Dun, Kim; Van Dam, Debby; De Deyn, Peter P.; Brysbaert, Marc; Marien, Peter

    To test the hypothesis of crossed cerebro-cerebellar language dominance (Marien, Engelborghs, Fabbro, & De Deyn, 2001) in atypical populations, the pattern of cerebral and cerebellar language organization in a right-handed woman with a large porencephalic cyst in the left temporal lobe with no

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

    Science.gov (United States)

    Verly, Marjolein; Verhoeven, Judith; Zink, Inge; Mantini, Dante; Peeters, Ronald; Deprez, Sabine; Emsell, Louise; Boets, Bart; Noens, Ilse; Steyaert, Jean; Lagae, Lieven; De Cock, Paul; Rommel, Nathalie; Sunaert, Stefan

    2014-01-01

    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. PMID:24567909

  15. Bilingualism increases neural response consistency and attentional control: evidence for sensory and cognitive coupling.

    Science.gov (United States)

    Krizman, Jennifer; Skoe, Erika; Marian, Viorica; Kraus, Nina

    2014-01-01

    Auditory processing is presumed to be influenced by cognitive processes - including attentional control - in a top-down manner. In bilinguals, activation of both languages during daily communication hones inhibitory skills, which subsequently bolster attentional control. We hypothesize that the heightened attentional demands of bilingual communication strengthens connections between cognitive (i.e., attentional control) and auditory processing, leading to greater across-trial consistency in the auditory evoked response (i.e., neural consistency) in bilinguals. To assess this, we collected passively-elicited auditory evoked responses to the syllable [da] in adolescent Spanish-English bilinguals and English monolinguals and separately obtained measures of attentional control and language ability. Bilinguals demonstrated enhanced attentional control and more consistent brainstem and cortical responses. In bilinguals, but not monolinguals, brainstem consistency tracked with language proficiency and attentional control. We interpret these enhancements in neural consistency as the outcome of strengthened attentional control that emerged from experience communicating in two languages. Copyright © 2013 Elsevier Inc. All rights reserved.

  16. LSTM, GRU, Highway and a Bit of Attention: An Empirical Overview for Language Modeling in Speech Recognition

    Science.gov (United States)

    2016-09-12

    R. K. Srivastava, K. Greff, and J. Schmidhuber, “Training very deep networks,” in Advances in Neural Information Processing Systems (NIPS), Montreal...modeling,” in Deep Learning workshop at Conf. on Advances in Neural Infor- mation Processing Systems (NIPS), Montreal, Canada, Dec. 2014. [19] R...Language Processing (EMNLP), Lisbon, Portugal, Sep. 2015, pp. 1412–1421. [38] K. Tran, A. Bisazza, and C. Monz, “Recurrent memory network for language

  17. Cross-language and second language speech perception

    DEFF Research Database (Denmark)

    Bohn, Ocke-Schwen

    2017-01-01

    in cross-language and second language speech perception research: The mapping issue (the perceptual relationship of sounds of the native and the nonnative language in the mind of the native listener and the L2 learner), the perceptual and learning difficulty/ease issue (how this relationship may or may...... not cause perceptual and learning difficulty), and the plasticity issue (whether and how experience with the nonnative language affects the perceptual organization of speech sounds in the mind of L2 learners). One important general conclusion from this research is that perceptual learning is possible at all...

  18. Implicit memory in music and language.

    Science.gov (United States)

    Ettlinger, Marc; Margulis, Elizabeth H; Wong, Patrick C M

    2011-01-01

    Research on music and language in recent decades has focused on their overlapping neurophysiological, perceptual, and cognitive underpinnings, ranging from the mechanism for encoding basic auditory cues to the mechanism for detecting violations in phrase structure. These overlaps have most often been identified in musicians with musical knowledge that was acquired explicitly, through formal training. In this paper, we review independent bodies of work in music and language that suggest an important role for implicitly acquired knowledge, implicit memory, and their associated neural structures in the acquisition of linguistic or musical grammar. These findings motivate potential new work that examines music and language comparatively in the context of the implicit memory system.

  19. Implicit Memory in Music and Language

    Directory of Open Access Journals (Sweden)

    Marc eEttlinger

    2011-09-01

    Full Text Available Research on music and language in recent decades has focused on their overlapping neurophysiological, perceptual, and cognitive underpinnings, ranging from the mechanism for encoding basic auditory cues to the mechanism for detecting violations in phrase structure. These overlaps have most often been identified in musicians with musical knowledge that was acquired explicitly, through formal training. In this paper, we review independent bodies of work in music and language that suggest an important role for implicitly acquired knowledge, implicit memory, and their associated neural structures in the acquisition of linguistic or musical grammar. These findings motivate potential new work that examines music and language comparatively in the context of the implicit memory system.

  20. Handwritten Javanese Character Recognition Using Several Artificial Neural Network Methods

    Directory of Open Access Journals (Sweden)

    Gregorius Satia Budhi

    2015-07-01

    Full Text Available Javanese characters are traditional characters that are used to write the Javanese language. The Javanese language is a language used by many people on the island of Java, Indonesia. The use of Javanese characters is diminishing more and more because of the difficulty of studying the Javanese characters themselves. The Javanese character set consists of basic characters, numbers, complementary characters, and so on. In this research we have developed a system to recognize Javanese characters. Input for the system is a digital image containing several handwritten Javanese characters. Preprocessing and segmentation are performed on the input image to get each character. For each character, feature extraction is done using the ICZ-ZCZ method. The output from feature extraction will become input for an artificial neural network. We used several artificial neural networks, namely a bidirectional associative memory network, a counterpropagation network, an evolutionary network, a backpropagation network, and a backpropagation network combined with chi2. From the experimental results it can be seen that the combination of chi2 and backpropagation achieved better recognition accuracy than the other methods.

  1. Diagnosis of aphasia using neural and fuzzy techniques

    DEFF Research Database (Denmark)

    Jantzen, Jan; Axer, H.; Keyserlingk, D. Graf von

    2000-01-01

    The language disability Aphasia has several sub-diagnoses such as Amnestic, Broca, Global, and Wernicke. Data concerning 265 patients is available in the form of test scores and diagnoses, made by physicians according to the Aachen Aphasia Test. A neural network model has been built, which...

  2. Diagnosis Of Aphasia Using Neural And Fuzzy Techniques

    DEFF Research Database (Denmark)

    Jantzen, Jan; Axer, Hubertus; Keyserlingk, Diedrich Graf von

    2002-01-01

    The language disability aphasia has several sub-diagnoses such as Amnestic, Broca, Global, and Wernicke. Data concerning 265 patients is available in the form of test scores and diagnoses, made by physicians according to the Aachen Aphasia Test. A neural network model has been built, which...

  3. Prediction of activity coefficients at infinite dilution for organic solutes in ionic liquids by artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Nami, Faezeh [Department of Chemistry, Shahid Beheshti University, G.C., Evin-Tehran 1983963113 (Iran, Islamic Republic of); Deyhimi, Farzad, E-mail: f-deyhimi@sbu.ac.i [Department of Chemistry, Shahid Beheshti University, G.C., Evin-Tehran 1983963113 (Iran, Islamic Republic of)

    2011-01-15

    To our knowledge, this work illustrates for the first time the ability of artificial neural network (ANN) to predict activity coefficients at infinite dilution for organic solutes in ionic liquids (ILs). Activity coefficient at infinite dilution ({gamma}{sup {infinity}}) is a useful parameter which can be used for the selection of effective solvent in the separation processes. Using a multi-layer feed-forward network with Levenberg-Marquardt optimization algorithm, the resulting ANN model generated activity coefficient at infinite dilution data over a temperature range of 298 to 363 K. The unavailable input data concerning softness (S) of organic compounds (solutes) and dipole moment ({mu}) of ionic liquids were calculated using GAMESS suites of quantum chemistry programs. The resulting ANN model and its validation are based on the investigation of up to 24 structurally different organic compounds (alkanes, alkenes, alkynes, cycloalkanes, aromatics, and alcohols) in 16 common imidazolium-based ionic liquids, at different temperatures within the range of 298 to 363 K (i.e. a total number of 914 {gamma}{sub Solute}{sup {infinity}}for each IL data point). The results show a satisfactory agreement between the predicted ANN and experimental data, where, the root mean square error (RMSE) and the determination coefficient (R{sup 2}) of the designed neural network were found to be 0.103, 0.996 for training data and 0.128, 0.994 for testing data, respectively.

  4. Prediction of activity coefficients at infinite dilution for organic solutes in ionic liquids by artificial neural network

    International Nuclear Information System (INIS)

    Nami, Faezeh; Deyhimi, Farzad

    2011-01-01

    To our knowledge, this work illustrates for the first time the ability of artificial neural network (ANN) to predict activity coefficients at infinite dilution for organic solutes in ionic liquids (ILs). Activity coefficient at infinite dilution (γ ∞ ) is a useful parameter which can be used for the selection of effective solvent in the separation processes. Using a multi-layer feed-forward network with Levenberg-Marquardt optimization algorithm, the resulting ANN model generated activity coefficient at infinite dilution data over a temperature range of 298 to 363 K. The unavailable input data concerning softness (S) of organic compounds (solutes) and dipole moment (μ) of ionic liquids were calculated using GAMESS suites of quantum chemistry programs. The resulting ANN model and its validation are based on the investigation of up to 24 structurally different organic compounds (alkanes, alkenes, alkynes, cycloalkanes, aromatics, and alcohols) in 16 common imidazolium-based ionic liquids, at different temperatures within the range of 298 to 363 K (i.e. a total number of 914 γ Solute ∞ for each IL data point). The results show a satisfactory agreement between the predicted ANN and experimental data, where, the root mean square error (RMSE) and the determination coefficient (R 2 ) of the designed neural network were found to be 0.103, 0.996 for training data and 0.128, 0.994 for testing data, respectively.

  5. A common neural substrate for language production and verbal working memory.

    Science.gov (United States)

    Acheson, Daniel J; Hamidi, Massihullah; Binder, Jeffrey R; Postle, Bradley R

    2011-06-01

    Verbal working memory (VWM), the ability to maintain and manipulate representations of speech sounds over short periods, is held by some influential models to be independent from the systems responsible for language production and comprehension [e.g., Baddeley, A. D. Working memory, thought, and action. New York, NY: Oxford University Press, 2007]. We explore the alternative hypothesis that maintenance in VWM is subserved by temporary activation of the language production system [Acheson, D. J., & MacDonald, M. C. Verbal working memory and language production: Common approaches to the serial ordering of verbal information. Psychological Bulletin, 135, 50-68, 2009b]. Specifically, we hypothesized that for stimuli lacking a semantic representation (e.g., nonwords such as mun), maintenance in VWM can be achieved by cycling information back and forth between the stages of phonological encoding and articulatory planning. First, fMRI was used to identify regions associated with two different stages of language production planning: the posterior superior temporal gyrus (pSTG) for phonological encoding (critical for VWM of nonwords) and the middle temporal gyrus (MTG) for lexical-semantic retrieval (not critical for VWM of nonwords). Next, in the same subjects, these regions were targeted with repetitive transcranial magnetic stimulation (rTMS) during language production and VWM task performance. Results showed that rTMS to the pSTG, but not the MTG, increased error rates on paced reading (a language production task) and on delayed serial recall of nonwords (a test of VWM). Performance on a lexical-semantic retrieval task (picture naming), in contrast, was significantly sensitive to rTMS of the MTG. Because rTMS was guided by language production-related activity, these results provide the first causal evidence that maintenance in VWM directly depends on the long-term representations and processes used in speech production.

  6. Differential receptive field organizations give rise to nearly identical neural correlations across three parallel sensory maps in weakly electric fish.

    Science.gov (United States)

    Hofmann, Volker; Chacron, Maurice J

    2017-09-01

    Understanding how neural populations encode sensory information thereby leading to perception and behavior (i.e., the neural code) remains an important problem in neuroscience. When investigating the neural code, one must take into account the fact that neural activities are not independent but are actually correlated with one another. Such correlations are seen ubiquitously and have a strong impact on neural coding. Here we investigated how differences in the antagonistic center-surround receptive field (RF) organization across three parallel sensory maps influence correlations between the activities of electrosensory pyramidal neurons. Using a model based on known anatomical differences in receptive field center size and overlap, we initially predicted large differences in correlated activity across the maps. However, in vivo electrophysiological recordings showed that, contrary to modeling predictions, electrosensory pyramidal neurons across all three segments displayed nearly identical correlations. To explain this surprising result, we incorporated the effects of RF surround in our model. By systematically varying both the RF surround gain and size relative to that of the RF center, we found that multiple RF structures gave rise to similar levels of correlation. In particular, incorporating known physiological differences in RF structure between the three maps in our model gave rise to similar levels of correlation. Our results show that RF center overlap alone does not determine correlations which has important implications for understanding how RF structure influences correlated neural activity.

  7. Dynamic concision for three-dimensional reconstruction of human organ built with virtual reality modelling language (VRML)*

    OpenAIRE

    Yu, Zheng-yang; Zheng, Shu-sen; Chen, Lei-ting; He, Xiao-qian; Wang, Jian-jun

    2005-01-01

    This research studies the process of 3D reconstruction and dynamic concision based on 2D medical digital images using virtual reality modelling language (VRML) and JavaScript language, with a focus on how to realize the dynamic concision of 3D medical model with script node and sensor node in VRML. The 3D reconstruction and concision of body internal organs can be built with such high quality that they are better than those obtained from the traditional methods. With the function of dynamic c...

  8. Community-level Language Planning for Chinese Heritage Language Maintenance in the United States

    Directory of Open Access Journals (Sweden)

    An Chung Cheng

    2012-08-01

    Full Text Available This paper investigates the development of Chinese heritage language in the United States from the perspective of language policy and planning. The case study examines the Chinese heritage language maintenance through community-based Chinese schools (CHS, and CHS’s relationships with Chinese American community, as well as governments and non-government organizations in China, Taiwan, and the United States. The paper starts with a theoretical discussion on the definition of language policy and planning, and then describes the history and heritage language education of Chinese Americans in the United States. The paper also presents micro-level planning activities initiated by CHSs in the Chinese American community and non-government organizations. Special focus is placed on the interaction between non-government organizations in the US and governmental bodies in Taiwan and mainland China and in the United States. This paper suggests that micro planning of heritage language maintenance is beneficial when initiated in the community, but it can only be developed and sustained within the wider scope of macro-level planning from governments

  9. Neural-Network Object-Recognition Program

    Science.gov (United States)

    Spirkovska, L.; Reid, M. B.

    1993-01-01

    HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.

  10. American Sign Language Alphabet Recognition Using a Neuromorphic Sensor and an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Miguel Rivera-Acosta

    2017-09-01

    Full Text Available This paper reports the design and analysis of an American Sign Language (ASL alphabet translation system implemented in hardware using a Field-Programmable Gate Array. The system process consists of three stages, the first being the communication with the neuromorphic camera (also called Dynamic Vision Sensor, DVS sensor using the Universal Serial Bus protocol. The feature extraction of the events generated by the DVS is the second part of the process, consisting of a presentation of the digital image processing algorithms developed in software, which aim to reduce redundant information and prepare the data for the third stage. The last stage of the system process is the classification of the ASL alphabet, achieved with a single artificial neural network implemented in digital hardware for higher speed. The overall result is the development of a classification system using the ASL signs contour, fully implemented in a reconfigurable device. The experimental results consist of a comparative analysis of the recognition rate among the alphabet signs using the neuromorphic camera in order to prove the proper operation of the digital image processing algorithms. In the experiments performed with 720 samples of 24 signs, a recognition accuracy of 79.58% was obtained.

  11. Language and Culture

    Science.gov (United States)

    Kramsch, Claire

    2014-01-01

    This paper surveys the research methods and approaches used in the multidisciplinary field of applied language studies or language education over the last fourty years. Drawing on insights gained in psycho- and sociolinguistics, educational linguistics and linguistic anthropology with regard to language and culture, it is organized around five…

  12. High school music classes enhance the neural processing of speech

    OpenAIRE

    Tierney, Adam; Krizman, Jennifer; Skoe, Erika; Johnston, Kathleen; Kraus, Nina

    2013-01-01

    Should music be a priority in public education? One argument for teaching music in school is that private music instruction relates to enhanced language abilities and neural function. However, the directionality of this relationship is unclear and it is unknown whether school-based music training can produce these enhancements. Here we show that two years of group music classes in high school enhance the subcortical encoding of speech. To tease apart the relationships between music and neural...

  13. Bi-directional LSTM Recurrent Neural Network for Chinese Word Segmentation

    OpenAIRE

    Yao, Yushi; Huang, Zheng

    2016-01-01

    Recurrent neural network(RNN) has been broadly applied to natural language processing(NLP) problems. This kind of neural network is designed for modeling sequential data and has been testified to be quite efficient in sequential tagging tasks. In this paper, we propose to use bi-directional RNN with long short-term memory(LSTM) units for Chinese word segmentation, which is a crucial preprocess task for modeling Chinese sentences and articles. Classical methods focus on designing and combining...

  14. Abnormal language-related oscillatory responses in primary progressive aphasia

    Directory of Open Access Journals (Sweden)

    A. Kielar

    Full Text Available Patients with Primary Progressive Aphasia (PPA may react to linguistic stimuli differently than healthy controls, reflecting degeneration of language networks and engagement of compensatory mechanisms. We used magnetoencephalography (MEG to evaluate oscillatory neural responses in sentence comprehension, in patients with PPA and age-matched controls. Participants viewed sentences containing semantically and syntactically anomalous words that evoke distinct oscillatory responses. For age-matched controls, semantic anomalies elicited left-lateralized 8–30 Hz power decreases distributed along ventral brain regions, whereas syntactic anomalies elicited bilateral power decreases in both ventral and dorsal regions. In comparison to controls, patients with PPA showed altered patterns of induced oscillations, characterized by delayed latencies and attenuated amplitude, which were correlated with linguistic impairment measured offline. The recruitment of right hemisphere temporo-parietal areas (also found in controls was correlated with preserved semantic processing abilities, indicating that preserved neural activity in these regions was able to support successful semantic processing. In contrast, syntactic processing was more consistently impaired in PPA, regardless of neural activity patterns, suggesting that this domain of language is particularly vulnerable to the neuronal loss. In addition, we found that delayed peak latencies of oscillatory responses were associated with lower accuracy for detecting semantic anomalies, suggesting that language deficits observed in PPA may be linked to delayed or slowed information processing. Keywords: MEG oscillations, Primary progressive aphasia (PPA, Sentence comprehension

  15. 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.

  16. Phonematic translation of Polish texts by the neural network

    International Nuclear Information System (INIS)

    Bielecki, A.; Podolak, I.T.; Wosiek, J.; Majkut, E.

    1996-01-01

    Using the back propagation algorithm, we have trained the feed forward neural network to pronounce Polish language, more precisely to translate Polish text into its phonematic counterpart. Depending on the input coding and network architecture, 88%-95% translation efficiency was achieved. (author)

  17. Extending Deacon’s Notion of Teleodynamics to Culture, Language, Organization, Science, Economics and Technology (CLOSET

    Directory of Open Access Journals (Sweden)

    Robert K. Logan

    2015-10-01

    Full Text Available Terrence Deacon’s (2012 notion developed in his book Incomplete Nature (IN that living organisms are teleodynamic systems that are self-maintaining, self-correcting and self-reproducing is extended to human social systems. The hypothesis is developed that culture, language, organization, science, economics and technology (CLOSET can be construed as living organisms that evolve, maintain and reproduce themselves and are self-correcting, and hence are teleodynamic systems. The elements of CLOSET are to a certain degree autonomous, even though they are obligate symbionts dependent on their human hosts for the energy that sustains them.

  18. Neurally adjusted ventilatory assist decreases ventilator-induced lung injury and non-pulmonary organ dysfunction in rabbits with acute lung injury

    NARCIS (Netherlands)

    Brander, Lukas; Sinderby, Christer; Lecomte, François; Leong-Poi, Howard; Bell, David; Beck, Jennifer; Tsoporis, James N.; Vaschetto, Rosanna; Schultz, Marcus J.; Parker, Thomas G.; Villar, Jesús; Zhang, Haibo; Slutsky, Arthur S.

    2009-01-01

    OBJECTIVE: To determine if neurally adjusted ventilatory assist (NAVA) that delivers pressure in proportion to diaphragm electrical activity is as protective to acutely injured lungs (ALI) and non-pulmonary organs as volume controlled (VC), low tidal volume (Vt), high positive end-expiratory

  19. Neural Control of the Immune System

    Science.gov (United States)

    Sundman, Eva; Olofsson, Peder S.

    2014-01-01

    Neural reflexes support homeostasis by modulating the function of organ systems. Recent advances in neuroscience and immunology have revealed that neural reflexes also regulate the immune system. Activation of the vagus nerve modulates leukocyte cytokine production and alleviates experimental shock and autoimmune disease, and recent data have…

  20. Does bilingualism contribute to cognitive reserve? Cognitive and neural perspectives.

    Science.gov (United States)

    Guzmán-Vélez, Edmarie; Tranel, Daniel

    2015-01-01

    Cognitive reserve refers to how individuals actively utilize neural resources to cope with neuropathology to maintain cognitive functioning. The present review aims to critically examine the literature addressing the relationship between bilingualism and cognitive reserve to elucidate whether bilingualism delays the onset of cognitive and behavioral manifestations of dementia. Potential neural mechanisms behind this relationship are discussed. PubMed and PsycINFO databases were searched (through January 2014) for original research articles in English or Spanish languages. The following search strings were used as keywords for study retrieval: "bilingual AND reserve," "reserve AND neural mechanisms," and "reserve AND multilingualism." Growing scientific evidence suggests that lifelong bilingualism contributes to cognitive reserve and delays the onset of Alzheimer's disease symptoms, allowing bilingual individuals affected by Alzheimer's disease to live an independent and richer life for a longer time than their monolingual counterparts. Lifelong bilingualism is related to more efficient use of brain resources that help individuals maintain cognitive functioning in the presence of neuropathology. We propose multiple putative neural mechanisms through which lifelong bilinguals cope with neuropathology. The roles of immigration status, education, age of onset, proficiency, and frequency of language use on the relationship between cognitive reserve and bilingualism are considered. Implications of these results for preventive practices and future research are discussed. PsycINFO Database Record (c) 2015 APA, all rights reserved.

  1. Does Bilingualism Contribute to Cognitive Reserve? Cognitive and Neural Perspectives

    Science.gov (United States)

    Guzmán-Vélez, Edmarie; Tranel, Daniel

    2015-01-01

    Objective Cognitive reserve refers to how individuals actively utilize neural resources to cope with neuropathology in order to maintain cognitive functioning. The present review aims to critically examine the literature addressing the relationship between bilingualism and cognitive reserve in order to elucidate whether bilingualism delays the onset of cognitive and behavioral manifestations of dementia. Potential neural mechanisms behind this relationship are discussed. Method Pubmed and PsychINFO databases were searched (through January 2014) for original research articles in English or Spanish languages. The following search strings were employed as keywords for study retrieval: ‘bilingual AND reserve’, ‘reserve AND neural mechanisms’, and ‘reserve AND multilingualism’. Results Growing scientific evidence suggests that lifelong bilingualism contributes to cognitive reserve and delays the onset of Alzheimer's disease symptoms, allowing bilingual individuals affected by Alzheimer's disease to live an independent and richer life for a longer time than their monolingual counterparts. Lifelong bilingualism is related to more efficient use of brain resources that help individuals maintain cognitive functioning in the presence of neuropathology. We propose multiple putative neural mechanisms through which lifelong bilinguals cope with neuropathology. The roles of immigration status, education, age of onset, proficiency and frequency of language use on the relationship between cognitive reserve and bilingualism are considered. Conclusions Implications of these results for preventive practices and future research are discussed. PMID:24933492

  2. A neural population model incorporating dopaminergic neurotransmission during complex voluntary behaviors.

    Directory of Open Access Journals (Sweden)

    Stefan Fürtinger

    2014-11-01

    Full Text Available Assessing brain activity during complex voluntary motor behaviors that require the recruitment of multiple neural sites is a field of active research. Our current knowledge is primarily based on human brain imaging studies that have clear limitations in terms of temporal and spatial resolution. We developed a physiologically informed non-linear multi-compartment stochastic neural model to simulate functional brain activity coupled with neurotransmitter release during complex voluntary behavior, such as speech production. Due to its state-dependent modulation of neural firing, dopaminergic neurotransmission plays a key role in the organization of functional brain circuits controlling speech and language and thus has been incorporated in our neural population model. A rigorous mathematical proof establishing existence and uniqueness of solutions to the proposed model as well as a computationally efficient strategy to numerically approximate these solutions are presented. Simulated brain activity during the resting state and sentence production was analyzed using functional network connectivity, and graph theoretical techniques were employed to highlight differences between the two conditions. We demonstrate that our model successfully reproduces characteristic changes seen in empirical data between the resting state and speech production, and dopaminergic neurotransmission evokes pronounced changes in modeled functional connectivity by acting on the underlying biological stochastic neural model. Specifically, model and data networks in both speech and rest conditions share task-specific network features: both the simulated and empirical functional connectivity networks show an increase in nodal influence and segregation in speech over the resting state. These commonalities confirm that dopamine is a key neuromodulator of the functional connectome of speech control. Based on reproducible characteristic aspects of empirical data, we suggest a number

  3. Signed language and human action processing: evidence for functional constraints on the human mirror-neuron system.

    Science.gov (United States)

    Corina, David P; Knapp, Heather Patterson

    2008-12-01

    In the quest to further understand the neural underpinning of human communication, researchers have turned to studies of naturally occurring signed languages used in Deaf communities. The comparison of the commonalities and differences between spoken and signed languages provides an opportunity to determine core neural systems responsible for linguistic communication independent of the modality in which a language is expressed. The present article examines such studies, and in addition asks what we can learn about human languages by contrasting formal visual-gestural linguistic systems (signed languages) with more general human action perception. To understand visual language perception, it is important to distinguish the demands of general human motion processing from the highly task-dependent demands associated with extracting linguistic meaning from arbitrary, conventionalized gestures. This endeavor is particularly important because theorists have suggested close homologies between perception and production of actions and functions of human language and social communication. We review recent behavioral, functional imaging, and neuropsychological studies that explore dissociations between the processing of human actions and signed languages. These data suggest incomplete overlap between the mirror-neuron systems proposed to mediate human action and language.

  4. Neuroplasticity associated with tactile language communication in a deaf-blind subject

    Directory of Open Access Journals (Sweden)

    Souzana Obretenova

    2010-01-01

    Full Text Available A longstanding debate in cognitive neuroscience pertains to the innate nature of language development and the underlying factors that determine this faculty. We explored the neural correlates associated with language processing in a unique individual who is early blind, congenitally deaf, and possesses a high level of language function. Using functional magnetic resonance imaging (fMRI, we compared the neural networks associated with the tactile reading of words presented in Braille, Print on Palm (POP, and a haptic form of American Sign Language (haptic ASL or hASL. With all three modes of tactile communication, indentifying words was associated with robust activation within occipital cortical regions as well as posterior superior temporal and inferior frontal language areas (lateralized within the left hemisphere. In a normally sighted and hearing interpreter, identifying words through hASL was associated with left-lateralized activation of inferior frontal language areas however robust occipital cortex activation was not observed. Diffusion tensor imaging (DTI-based tractography revealed differences consistent with enhanced occipital-temporal connectivity in the deaf-blind subject. Our results demonstrate that in the case of early onset of both visual and auditory deprivation, tactile-based communication is associated with an extensive cortical network implicating occipital as well as posterior superior temporal and frontal associated language areas. The cortical areas activated in this deaf-blind subject are consistent with characteristic cortical regions previously implicated with language. Finally, the resilience of language function within the context of early and combined visual and auditory deprivation may be related to enhanced connectivity between relevant cortical areas.

  5. Deep Neural Network-Based Chinese Semantic Role Labeling

    Institute of Scientific and Technical Information of China (English)

    ZHENG Xiaoqing; CHEN Jun; SHANG Guoqiang

    2017-01-01

    A recent trend in machine learning is to use deep architec-tures to discover multiple levels of features from data, which has achieved impressive results on various natural language processing (NLP) tasks. We propose a deep neural network-based solution to Chinese semantic role labeling (SRL) with its application on message analysis. The solution adopts a six-step strategy: text normalization, named entity recognition (NER), Chinese word segmentation and part-of-speech (POS) tagging, theme classification, SRL, and slot filling. For each step, a novel deep neural network - based model is designed and optimized, particularly for smart phone applications. Ex-periment results on all the NLP sub - tasks of the solution show that the proposed neural networks achieve state-of-the-art performance with the minimal computational cost. The speed advantage of deep neural networks makes them more competitive for large-scale applications or applications requir-ing real-time response, highlighting the potential of the pro-posed solution for practical NLP systems.

  6. A Constructive Neural-Network Approach to Modeling Psychological Development

    Science.gov (United States)

    Shultz, Thomas R.

    2012-01-01

    This article reviews a particular computational modeling approach to the study of psychological development--that of constructive neural networks. This approach is applied to a variety of developmental domains and issues, including Piagetian tasks, shift learning, language acquisition, number comparison, habituation of visual attention, concept…

  7. Neuroscience illuminating the influence of auditory or phonological intervention on language-related deficits

    Directory of Open Access Journals (Sweden)

    Sari eYlinen

    2015-02-01

    Full Text Available Remediation programs for language-related learning deficits are urgently needed to enable equal opportunities in education. To meet this need, different training and intervention programs have been developed. Here we review, from an educational perspective, studies that have explored the neural basis of behavioral changes induced by auditory or phonological training in dyslexia, specific language impairment (SLI, and language-learning impairment (LLI. Training has been shown to induce plastic changes in deficient neural networks. In dyslexia, these include, most consistently, increased or normalized activation of previously hypoactive inferior frontal and occipito-temporal areas. In SLI and LLI, studies have shown the strengthening of previously weak auditory brain responses as a result of training. The combination of behavioral and brain measures of remedial gains has potential to increase the understanding of the causes of language-related deficits, which may help to target remedial interventions more accurately to the core problem.

  8. 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.

  9. Artificial neural network with self-organizing mapping for reactor stability monitoring

    International Nuclear Information System (INIS)

    Okumura, Motofumi; Tsuji, Masashi; Shimazu, Yoichiro; Narabayashi, Tadashi

    2008-01-01

    In BWR stability monitoring damping ratio has been used as a stability index. A method for estimating the damping ratio by applying Principal Component Analysis (PCA) to neutron detector signals measured with local power range monitors (LPRMs) had been developed; In this method, measured fluctuating signal is decomposed into some independent components and the signal component directly related to stability is extracted among them to determine the damping ratio. For online monitoring, it is necessary to select stability related signal component efficiently. The self-organizing map (SOM) is one of the artificial neural networks and has the characteristics such that online learning is possible without supervised learning within a relatively short time. In the present study, the SOM was applied to extract the relevant signal component more quickly and more accurately, and the availability was confirmed through the feasibility study. (author)

  10. Neural Architectures for Control

    Science.gov (United States)

    Peterson, James K.

    1991-01-01

    The cerebellar model articulated controller (CMAC) neural architectures are shown to be viable for the purposes of real-time learning and control. Software tools for the exploration of CMAC performance are developed for three hardware platforms, the MacIntosh, the IBM PC, and the SUN workstation. All algorithm development was done using the C programming language. These software tools were then used to implement an adaptive critic neuro-control design that learns in real-time how to back up a trailer truck. The truck backer-upper experiment is a standard performance measure in the neural network literature, but previously the training of the controllers was done off-line. With the CMAC neural architectures, it was possible to train the neuro-controllers on-line in real-time on a MS-DOS PC 386. CMAC neural architectures are also used in conjunction with a hierarchical planning approach to find collision-free paths over 2-D analog valued obstacle fields. The method constructs a coarse resolution version of the original problem and then finds the corresponding coarse optimal path using multipass dynamic programming. CMAC artificial neural architectures are used to estimate the analog transition costs that dynamic programming requires. The CMAC architectures are trained in real-time for each obstacle field presented. The coarse optimal path is then used as a baseline for the construction of a fine scale optimal path through the original obstacle array. These results are a very good indication of the potential power of the neural architectures in control design. In order to reach as wide an audience as possible, we have run a seminar on neuro-control that has met once per week since 20 May 1991. This seminar has thoroughly discussed the CMAC architecture, relevant portions of classical control, back propagation through time, and adaptive critic designs.

  11. Beyond the language given: The neural correlates of inferring speaker meaning

    NARCIS (Netherlands)

    Bašnáková, J.; Weber, K.; Petersson, K.M.; van Berkum, J.J.A.; Hagoort, P.

    2014-01-01

    Even though language allows us to say exactly what we mean, we often use language to say things indirectly, in a way that depends on the specific communicative context. For example, we can use an apparently straightforward sentence like “It is hard to give a good presentation” to convey deeper

  12. Beyond the Language Given: The Neural Correlates of Inferring Speaker Meaning

    NARCIS (Netherlands)

    Basnakova, J.; Weber, K.M.; Petersson, K.M.; Berkum, J.J.A. van; Hagoort, P.

    2014-01-01

    Even though language allows us to say exactly what we mean, we often use language to say things indirectly, in a way that depends on the specific communicative context. For example, we can use an apparently straightforward sentence like "It is hard to give a good presentation" to convey deeper

  13. Numerical exploration of the influence of neural noise on the ...

    Indian Academy of Sciences (India)

    PRAKASH KUMAR

    from the lack of detailed neural biophysical elements in the present simulation. ... of perception, the lack of knowledge of all these details is equally impressive. .... I would like to thank Carmen Gómez Sos for her English language editorial ...

  14. Multi-Lingual Deep Neural Networks for Language Recognition

    Science.gov (United States)

    2016-08-08

    system architecture 2. I-VECTOR SYSTEM Most state-of-the- art language recognition systems are based on the i-vector framework [8] depicted in Figure 1...may be possible to achieve more gains on the Arabic and Chinese cluster by adding ad- ditional ASR corpora such as Callhome Egyptian Arabic or HKUST

  15. 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.

  16. Infrared neural stimulation (INS) inhibits electrically evoked neural responses in the deaf white cat

    Science.gov (United States)

    Richter, Claus-Peter; Rajguru, Suhrud M.; Robinson, Alan; Young, Hunter K.

    2014-03-01

    Infrared neural stimulation (INS) has been used in the past to evoke neural activity from hearing and partially deaf animals. All the responses were excitatory. In Aplysia californica, Duke and coworkers demonstrated that INS also inhibits neural responses [1], which similar observations were made in the vestibular system [2, 3]. In deaf white cats that have cochleae with largely reduced spiral ganglion neuron counts and a significant degeneration of the organ of Corti, no cochlear compound action potentials could be observed during INS alone. However, the combined electrical and optical stimulation demonstrated inhibitory responses during irradiation with infrared light.

  17. 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.

  18. Continuous Chinese sign language recognition with CNN-LSTM

    Science.gov (United States)

    Yang, Su; Zhu, Qing

    2017-07-01

    The goal of sign language recognition (SLR) is to translate the sign language into text, and provide a convenient tool for the communication between the deaf-mute and the ordinary. In this paper, we formulate an appropriate model based on convolutional neural network (CNN) combined with Long Short-Term Memory (LSTM) network, in order to accomplish the continuous recognition work. With the strong ability of CNN, the information of pictures captured from Chinese sign language (CSL) videos can be learned and transformed into vector. Since the video can be regarded as an ordered sequence of frames, LSTM model is employed to connect with the fully-connected layer of CNN. As a recurrent neural network (RNN), it is suitable for sequence learning tasks with the capability of recognizing patterns defined by temporal distance. Compared with traditional RNN, LSTM has performed better on storing and accessing information. We evaluate this method on our self-built dataset including 40 daily vocabularies. The experimental results show that the recognition method with CNN-LSTM can achieve a high recognition rate with small training sets, which will meet the needs of real-time SLR system.

  19. The neural dynamics of competition resolution for language production in the prefrontal cortex.

    Science.gov (United States)

    Bourguignon, Nicolas J; Ohashi, Hiroki; Nguyen, Don; Gracco, Vincent L

    2018-03-01

    Previous research suggests a pivotal role of the prefrontal cortex (PFC) in word selection during tasks of confrontation naming (CN) and verb generation (VG), both of which feature varying degrees of competition between candidate responses. However, discrepancies in prefrontal activity have also been reported between the two tasks, in particular more widespread and intense activation in VG extending into (left) ventrolateral PFC, the functional significance of which remains unclear. We propose that these variations reflect differences in competition resolution processes tied to distinct underlying lexico-semantic operations: Although CN involves selecting lexical entries out of limited sets of alternatives, VG requires exploration of possible semantic relations not readily evident from the object itself, requiring prefrontal areas previously shown to be recruited in top-down retrieval of information from lexico-semantic memory. We tested this hypothesis through combined independent component analysis of functional imaging data and information-theoretic measurements of variations in selection competition associated with participants' performance in overt CN and VG tasks. Selection competition during CN engaged the anterior insula and surrounding opercular tissue, while competition during VG recruited additional activity of left ventrolateral PFC. These patterns remained after controlling for participants' speech onset latencies indicative of possible task differences in mental effort. These findings have implications for understanding the neural-computational dynamics of cognitive control in language production and how it relates to the functional architecture of adaptive behavior. © 2017 Wiley Periodicals, Inc.

  20. LANGUAGE EXPERIENCE SHAPES PROCESSING OF PITCH RELEVANT INFORMATION IN THE HUMAN BRAINSTEM AND AUDITORY CORTEX: ELECTROPHYSIOLOGICAL EVIDENCE.

    Science.gov (United States)

    Krishnan, Ananthanarayan; Gandour, Jackson T

    2014-12-01

    Pitch is a robust perceptual attribute that plays an important role in speech, language, and music. As such, it provides an analytic window to evaluate how neural activity relevant to pitch undergo transformation from early sensory to later cognitive stages of processing in a well coordinated hierarchical network that is subject to experience-dependent plasticity. We review recent evidence of language experience-dependent effects in pitch processing based on comparisons of native vs. nonnative speakers of a tonal language from electrophysiological recordings in the auditory brainstem and auditory cortex. We present evidence that shows enhanced representation of linguistically-relevant pitch dimensions or features at both the brainstem and cortical levels with a stimulus-dependent preferential activation of the right hemisphere in native speakers of a tone language. We argue that neural representation of pitch-relevant information in the brainstem and early sensory level processing in the auditory cortex is shaped by the perceptual salience of domain-specific features. While both stages of processing are shaped by language experience, neural representations are transformed and fundamentally different at each biological level of abstraction. The representation of pitch relevant information in the brainstem is more fine-grained spectrotemporally as it reflects sustained neural phase-locking to pitch relevant periodicities contained in the stimulus. In contrast, the cortical pitch relevant neural activity reflects primarily a series of transient temporal neural events synchronized to certain temporal attributes of the pitch contour. We argue that experience-dependent enhancement of pitch representation for Chinese listeners most likely reflects an interaction between higher-level cognitive processes and early sensory-level processing to improve representations of behaviorally-relevant features that contribute optimally to perception. It is our view that long

  1. Genetic algorithm-based neural network for accidents diagnosis of research reactors on FPGA

    International Nuclear Information System (INIS)

    Ghuname, A.A.A.

    2012-01-01

    The Nuclear Research Reactors plants are expected to be operated with high levels of reliability, availability and safety. In order to achieve and maintain system stability and assure satisfactory and safe operation, there is increasing demand for automated systems to detect and diagnose such failures. Artificial Neural Networks (ANNs) are one of the most popular solutions because of their parallel structure, high speed, and their ability to give easy solution to complicated problems. The genetic algorithms (GAs) which are search algorithms (optimization techniques), in recent years, have been used to find the optimum construction of a neural network for definite application, as one of the advantages of its usage. Nowadays, Field Programmable Gate Arrays (FPGAs) are being an important implementation method of neural networks due to their high performance and they can easily be made parallel. The VHDL, which stands for VHSIC (Very High Speed Integrated Circuits) Hardware Description Language, have been used to describe the design behaviorally in addition to schematic and other description languages. The description of designs in synthesizable language such as VHDL make them reusable and be implemented in upgradeable systems like the Nuclear Research Reactors plants. In this thesis, the work was carried out through three main parts.In the first part, the Nuclear Research Reactors accident's pattern recognition is tackled within the artificial neural network approach. Such patterns are introduced initially without noise. And, to increase the reliability of such neural network, the noise ratio up to 50% was added for training in order to ensure the recognition of these patterns if it introduced with noise.The second part is concerned with the construction of Artificial Neural Networks (ANNs) using Genetic algorithms (GAs) for the nuclear accidents diagnosis. MATLAB ANNs toolbox and GAs toolbox are employed to optimize an ANN for this purpose. The results obtained show

  2. High school music classes enhance the neural processing of speech.

    Science.gov (United States)

    Tierney, Adam; Krizman, Jennifer; Skoe, Erika; Johnston, Kathleen; Kraus, Nina

    2013-01-01

    Should music be a priority in public education? One argument for teaching music in school is that private music instruction relates to enhanced language abilities and neural function. However, the directionality of this relationship is unclear and it is unknown whether school-based music training can produce these enhancements. Here we show that 2 years of group music classes in high school enhance the neural encoding of speech. To tease apart the relationships between music and neural function, we tested high school students participating in either music or fitness-based training. These groups were matched at the onset of training on neural timing, reading ability, and IQ. Auditory brainstem responses were collected to a synthesized speech sound presented in background noise. After 2 years of training, the neural responses of the music training group were earlier than at pre-training, while the neural timing of students in the fitness training group was unchanged. These results represent the strongest evidence to date that in-school music education can cause enhanced speech encoding. The neural benefits of musical training are, therefore, not limited to expensive private instruction early in childhood but can be elicited by cost-effective group instruction during adolescence.

  3. Neural network recognition of mammographic lesions

    International Nuclear Information System (INIS)

    Oldham, W.J.B.; Downes, P.T.; Hunter, V.

    1987-01-01

    A method for recognition of mammographic lesions through the use of neural networks is presented. Neural networks have exhibited the ability to learn the shape andinternal structure of patterns. Digitized mammograms containing circumscribed and stelate lesions were used to train a feedfoward synchronous neural network that self-organizes to stable attractor states. Encoding of data for submission to the network was accomplished by performing a fractal analysis of the digitized image. This results in scale invariant representation of the lesions. Results are discussed

  4. The effect of the neural activity on topological properties of growing neural networks.

    Science.gov (United States)

    Gafarov, F M; Gafarova, V R

    2016-09-01

    The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

  5. What are the goals of language teaching?

    Directory of Open Access Journals (Sweden)

    Vivian Cook

    2013-01-01

    Full Text Available For many centuries people who speak more than one language, that is to say second language (L2 users, have been admired. In the 16th century an advisor to Elizabeth I of England said: ‘For even as a hawk flieth not high with one wing, even so a man reacheth not to excellency with one tongue.’ Roger Ascham, The Scholemaster, 1570 In the 21st century the education minister for Elizabeth II proclaimed: ‘It is literally the case that learning languages makes you smarter. The neural networks in the brain strengthen as a result of language learning.’ Michael Gove, UK Education Secretary, 2011 Yet, despite these public statements, bilingualism is more often seen as a problem to be solved than an asset to be developed. Second language (L2 users indeed have problems, whether social, psychological or economic – like everyone else. But few of these stem from their bilingualism itself.

  6. 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.

  7. Atypical cortical language organization in epilepsy patients: evidence for divergent hemispheric dominance for receptive and expressive language function.

    Science.gov (United States)

    Eliashiv, Dawn S; Kurelowech, Lacey; Quint, Patti; Chung, Jeffrey M; Otis, Shirley M; Gage, Nicole M

    2014-06-01

    The central goal of presurgical language mapping is to identify brain regions that subserve cortical language function to minimize postsurgical language deficits. Presurgical language mapping in patients with epilepsy presents a key challenge because of the atypical pattern of hemispheric language dominance found in this population, with higher incidences of bilateral and right-biased language dominance than typical. In this prospective study, we combine magnetoencephalography with a panel of tasks designed to separately assess receptive and expressive function to provide a sensitive measure of language function in 15 candidates for resective surgery. We report the following: 4 of 15 patients (27%) showed left hemisphere dominance across all tasks, 4 of 15 patients (27%) showed right hemisphere dominance across all tasks, and 7 of 15 (46%) showed discordant language dominance, with right-dominant receptive and left-dominant expressive language. All patients with discordant language dominance showed this right-receptive and left-expressive pattern. Results provide further evidence supporting the importance of using a panel of tasks to assess separable aspects of language function. The clinical relevance of the findings is discussed, especially about current clinical operative measures for assessing language dominance, which use single hemisphere procedure (intracarotid amobarbital procedure and awake intraoperative stimulation) for determining language laterality.

  8. Bilingual experience and resting-state brain connectivity: Impacts of L2 age of acquisition and social diversity of language use on control networks.

    Science.gov (United States)

    Gullifer, Jason W; Chai, Xiaoqian J; Whitford, Veronica; Pivneva, Irina; Baum, Shari; Klein, Denise; Titone, Debra

    2018-05-01

    We investigated the independent contributions of second language (L2) age of acquisition (AoA) and social diversity of language use on intrinsic brain organization using seed-based resting-state functional connectivity among highly proficient French-English bilinguals. There were two key findings. First, earlier L2 AoA related to greater interhemispheric functional connectivity between homologous frontal brain regions, and to decreased reliance on proactive executive control in an AX-Continuous Performance Task completed outside the scanner. Second, greater diversity in social language use in daily life related to greater connectivity between the anterior cingulate cortex and the putamen bilaterally, and to increased reliance on proactive control in the same task. These findings suggest that early vs. late L2 AoA links to a specialized neural framework for processing two languages that may engage a specific type of executive control (e.g., reactive control). In contrast, higher vs. lower degrees of diversity in social language use link to a broadly distributed set of brain networks implicated in proactive control and context monitoring. Copyright © 2018 Elsevier Ltd. All rights reserved.

  9. Neural encoding of the speech envelope by children with developmental dyslexia.

    Science.gov (United States)

    Power, Alan J; Colling, Lincoln J; Mead, Natasha; Barnes, Lisa; Goswami, Usha

    2016-09-01

    Developmental dyslexia is consistently associated with difficulties in processing phonology (linguistic sound structure) across languages. One view is that dyslexia is characterised by a cognitive impairment in the "phonological representation" of word forms, which arises long before the child presents with a reading problem. Here we investigate a possible neural basis for developmental phonological impairments. We assess the neural quality of speech encoding in children with dyslexia by measuring the accuracy of low-frequency speech envelope encoding using EEG. We tested children with dyslexia and chronological age-matched (CA) and reading-level matched (RL) younger children. Participants listened to semantically-unpredictable sentences in a word report task. The sentences were noise-vocoded to increase reliance on envelope cues. Envelope reconstruction for envelopes between 0 and 10Hz showed that the children with dyslexia had significantly poorer speech encoding in the 0-2Hz band compared to both CA and RL controls. These data suggest that impaired neural encoding of low frequency speech envelopes, related to speech prosody, may underpin the phonological deficit that causes dyslexia across languages. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  10. Neural network based system for script identification in Indian ...

    Indian Academy of Sciences (India)

    2016-08-26

    Aug 26, 2016 ... The paper describes a neural network-based script identification system which can be used in the machine reading of documents written in English, Hindi and Kannada language scripts. Script identification is a basic requirement in automation of document processing, in multi-script, multi-lingual ...

  11. Modelling of word usage frequency dynamics using artificial neural network

    International Nuclear Information System (INIS)

    Maslennikova, Yu S; Bochkarev, V V; Voloskov, D S

    2014-01-01

    In this paper the method for modelling of word usage frequency time series is proposed. An artificial feedforward neural network was used to predict word usage frequencies. The neural network was trained using the maximum likelihood criterion. The Google Books Ngram corpus was used for the analysis. This database provides a large amount of data on frequency of specific word forms for 7 languages. Statistical modelling of word usage frequency time series allows finding optimal fitting and filtering algorithm for subsequent lexicographic analysis and verification of frequency trend models

  12. 22nd Italian Workshop on Neural Nets

    CERN Document Server

    Bassis, Simone; Esposito, Anna; Morabito, Francesco

    2013-01-01

    This volume collects a selection of contributions which has been presented at the 22nd Italian Workshop on Neural Networks, the yearly meeting of the Italian Society for Neural Networks (SIREN). The conference was held in Italy, Vietri sul Mare (Salerno), during May 17-19, 2012. The annual meeting of SIREN is sponsored by International Neural Network Society (INNS), European Neural Network Society (ENNS) and IEEE Computational Intelligence Society (CIS). The book – as well as the workshop-  is organized in three main components, two special sessions and a group of regular sessions featuring different aspects and point of views of artificial neural networks and natural intelligence, also including applications of present compelling interest.

  13. Representation of linguistic form and function in recurrent neural networks

    NARCIS (Netherlands)

    Kadar, Akos; Chrupala, Grzegorz; Alishahi, Afra

    2017-01-01

    We present novel methods for analyzing the activation patterns of recurrent neural networks from a linguistic point of view and explore the types of linguistic structure they learn. As a case study, we use a standard standalone language model, and a multi-task gated recurrent network architecture

  14. Neural mechanisms of song memory formation in juvenile zebra finches

    NARCIS (Netherlands)

    Moorman, S.

    2015-01-01

    There are many parallels between the acquisition of spoken language in human infants and song learning in songbirds, at the behavioural, neural, genetic and cognitive levels. Both human infants and juvenile songbirds are able to imitate sounds from adults of the same species (often their parents),

  15. The functional neuroanatomy of language

    Science.gov (United States)

    Hickok, Gregory

    2009-09-01

    There has been substantial progress over the last several years in understanding aspects of the functional neuroanatomy of language. Some of these advances are summarized in this review. It will be argued that recognizing speech sounds is carried out in the superior temporal lobe bilaterally, that the superior temporal sulcus bilaterally is involved in phonological-level aspects of this process, that the frontal/motor system is not central to speech recognition although it may modulate auditory perception of speech, that conceptual access mechanisms are likely located in the lateral posterior temporal lobe (middle and inferior temporal gyri), that speech production involves sensory-related systems in the posterior superior temporal lobe in the left hemisphere, that the interface between perceptual and motor systems is supported by a sensory-motor circuit for vocal tract actions (not dedicated to speech) that is very similar to sensory-motor circuits found in primate parietal lobe, and that verbal short-term memory can be understood as an emergent property of this sensory-motor circuit. These observations are considered within the context of a dual stream model of speech processing in which one pathway supports speech comprehension and the other supports sensory-motor integration. Additional topics of discussion include the functional organization of the planum temporale for spatial hearing and speech-related sensory-motor processes, the anatomical and functional basis of a form of acquired language disorder, conduction aphasia, the neural basis of vocabulary development, and sentence-level/grammatical processing.

  16. Pragmatic Bootstrapping: A Neural Network Model of Vocabulary Acquisition

    Science.gov (United States)

    Caza, Gregory A.; Knott, Alistair

    2012-01-01

    The social-pragmatic theory of language acquisition proposes that children only become efficient at learning the meanings of words once they acquire the ability to understand the intentions of other agents, in particular the intention to communicate (Akhtar & Tomasello, 2000). In this paper we present a neural network model of word learning which…

  17. Lifetime prediction for organic coating under alternating hydrostatic pressure by artificial neural network

    Science.gov (United States)

    Tian, Wenliang; Meng, Fandi; Liu, Li; Li, Ying; Wang, Fuhui

    2017-01-01

    A concept for prediction of organic coatings, based on the alternating hydrostatic pressure (AHP) accelerated tests, has been presented. An AHP accelerated test with different pressure values has been employed to evaluate coating degradation. And a back-propagation artificial neural network (BP-ANN) has been established to predict the service property and the service lifetime of coatings. The pressure value (P), immersion time (t) and service property (impedance modulus |Z|) are utilized as the parameters of the network. The average accuracies of the predicted service property and immersion time by the established network are 98.6% and 84.8%, respectively. The combination of accelerated test and prediction method by BP-ANN is promising to evaluate and predict coating property used in deep sea. PMID:28094340

  18. APPLICATION OF A FULL-COHERENT ARTIFICIAL NEURAL NETWORK FOR FORECASTING OF THE MODES OF STORAGE OF DOMESTIC LOW-OLIVE RAW MATERIALS IN CONTROLLED ENVIRONMENTS

    Directory of Open Access Journals (Sweden)

    N. S. Rodionova

    2015-01-01

    Full Text Available Summary. Researches on increase in an expiration date of the wheat germs (WG with use of compositions of organic acids are conducted. With a research objective of influence of concentration of mixes of organic acids on change of indicators of quality at storage of the SALARY in various modes investigated quality indicators in the range of concentration of 1-7% to the mass of a product. As control the raw SALARIES served. Skilled products stored in refrigerator conditions (temperature 4-6 ºС, relative humidity of air of 75-80% and a warehouse (temperature 20-22 ºС, relative humidity of air of 70-80%. The software product on the basis of the program of training and the analysis of training of an artificial full-coherent neural network (INS in the Python 2.7 language with program libraries of mathematical processing of scientific data of "scipy" is developed. As input parameters of a neural network were considered: humidity of wheaten germs (х1, %, relative humidity of air (х2, %, ambient temperature (х3, ºС and concentration of mix of organic acids (х4, %. By means of the software, some neural networks were designed and trained. For modeling the network with two layers was used. Applying the developed and trained neural network it is possible constructed dependence у(х1, х2, х3, х4. For visualization in three-dimensional space limited amount of arguments of function by two. Results of work of neural networks y (x1, x4 with the recorded entrance parameters (x2 = 60, %, x3=20, ºC and a neural network y (x2, x3 with the recorded input parameters are presented (x1 = 15%, x4 = 5%. The received mathematical model which on the set set of certain parameters of storage, allows to receive concrete value of output parameter and to plan the storage modes in controlled environments.

  19. Modeling Language and Cognition with Deep Unsupervised Learning:A Tutorial Overview

    OpenAIRE

    Marco eZorzi; Marco eZorzi; Alberto eTestolin; Ivilin Peev Stoianov; Ivilin Peev Stoianov

    2013-01-01

    Deep unsupervised learning in stochastic recurrent neural networks with many layers of hidden units is a recent breakthrough in neural computation research. These networks build a hierarchy of progressively more complex distributed representations of the sensory data by fitting a hierarchical generative model. In this article we discuss the theoretical foundations of this approach and we review key issues related to training, testing and analysis of deep networks for modeling language and cog...

  20. Modeling language and cognition with deep unsupervised learning: a tutorial overview

    OpenAIRE

    Zorzi, Marco; Testolin, Alberto; Stoianov, Ivilin P.

    2013-01-01

    Deep unsupervised learning in stochastic recurrent neural networks with many layers of hidden units is a recent breakthrough in neural computation research. These networks build a hierarchy of progressively more complex distributed representations of the sensory data by fitting a hierarchical generative model. In this article we discuss the theoretical foundations of this approach and we review key issues related to training, testing and analysis of deep networks for modeling language and cog...

  1. "Neural overlap of L1 and L2 semantic representations across visual and auditory modalities: a decoding approach".

    Science.gov (United States)

    Van de Putte, Eowyn; De Baene, Wouter; Price, Cathy J; Duyck, Wouter

    2018-05-01

    This study investigated whether brain activity in Dutch-French bilinguals during semantic access to concepts from one language could be used to predict neural activation during access to the same concepts from another language, in different language modalities/tasks. This was tested using multi-voxel pattern analysis (MVPA), within and across language comprehension (word listening and word reading) and production (picture naming). It was possible to identify the picture or word named, read or heard in one language (e.g. maan, meaning moon) based on the brain activity in a distributed bilateral brain network while, respectively, naming, reading or listening to the picture or word in the other language (e.g. lune). The brain regions identified differed across tasks. During picture naming, brain activation in the occipital and temporal regions allowed concepts to be predicted across languages. During word listening and word reading, across-language predictions were observed in the rolandic operculum and several motor-related areas (pre- and postcentral, the cerebellum). In addition, across-language predictions during reading were identified in regions typically associated with semantic processing (left inferior frontal, middle temporal cortex, right cerebellum and precuneus) and visual processing (inferior and middle occipital regions and calcarine sulcus). Furthermore, across modalities and languages, the left lingual gyrus showed semantic overlap across production and word reading. These findings support the idea of at least partially language- and modality-independent semantic neural representations. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  2. A step beyond local observations with a dialog aware bidirectional GRU network for Spoken Language Understanding

    OpenAIRE

    Vukotic , Vedran; Raymond , Christian; Gravier , Guillaume

    2016-01-01

    International audience; Architectures of Recurrent Neural Networks (RNN) recently become a very popular choice for Spoken Language Understanding (SLU) problems; however, they represent a big family of different architectures that can furthermore be combined to form more complex neural networks. In this work, we compare different recurrent networks, such as simple Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM) networks, Gated Memory Units (GRU) and their bidirectional versions,...

  3. High level cognitive information processing in neural networks

    Science.gov (United States)

    Barnden, John A.; Fields, Christopher A.

    1992-01-01

    Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

  4. Neural Pattern Similarity in the Left IFG and Fusiform Is Associated with Novel Word Learning

    Directory of Open Access Journals (Sweden)

    Jing Qu

    2017-08-01

    Full Text Available Previous studies have revealed that greater neural pattern similarity across repetitions is associated with better subsequent memory. In this study, we used an artificial language training paradigm and representational similarity analysis to examine whether neural pattern similarity across repetitions before training was associated with post-training behavioral performance. Twenty-four native Chinese speakers were trained to learn a logographic artificial language for 12 days and behavioral performance was recorded using the word naming and picture naming tasks. Participants were scanned while performing a passive viewing task before training, after 4-day training and after 12-day training. Results showed that pattern similarity in the left pars opercularis (PO and fusiform gyrus (FG before training was negatively associated with reaction time (RT in both word naming and picture naming tasks after training. These results suggest that neural pattern similarity is an effective neurofunctional predictor of novel word learning in addition to word memory.

  5. Neural Pattern Similarity in the Left IFG and Fusiform Is Associated with Novel Word Learning

    Science.gov (United States)

    Qu, Jing; Qian, Liu; Chen, Chuansheng; Xue, Gui; Li, Huiling; Xie, Peng; Mei, Leilei

    2017-01-01

    Previous studies have revealed that greater neural pattern similarity across repetitions is associated with better subsequent memory. In this study, we used an artificial language training paradigm and representational similarity analysis to examine whether neural pattern similarity across repetitions before training was associated with post-training behavioral performance. Twenty-four native Chinese speakers were trained to learn a logographic artificial language for 12 days and behavioral performance was recorded using the word naming and picture naming tasks. Participants were scanned while performing a passive viewing task before training, after 4-day training and after 12-day training. Results showed that pattern similarity in the left pars opercularis (PO) and fusiform gyrus (FG) before training was negatively associated with reaction time (RT) in both word naming and picture naming tasks after training. These results suggest that neural pattern similarity is an effective neurofunctional predictor of novel word learning in addition to word memory. PMID:28878640

  6. Child gender influences paternal behavior, language, and brain function.

    Science.gov (United States)

    Mascaro, Jennifer S; Rentscher, Kelly E; Hackett, Patrick D; Mehl, Matthias R; Rilling, James K

    2017-06-01

    Multiple lines of research indicate that fathers often treat boys and girls differently in ways that impact child outcomes. The complex picture that has emerged, however, is obscured by methodological challenges inherent to the study of parental caregiving, and no studies to date have examined the possibility that gender differences in observed real-world paternal behavior are related to differential paternal brain responses to male and female children. Here we compare fathers of daughters and fathers of sons in terms of naturalistically observed everyday caregiving behavior and neural responses to child picture stimuli. Compared with fathers of sons, fathers of daughters were more attentively engaged with their daughters, sang more to their daughters, used more analytical language and language related to sadness and the body with their daughters, and had a stronger neural response to their daughter's happy facial expressions in areas of the brain important for reward and emotion regulation (medial and lateral orbitofrontal cortex [OFC]). In contrast, fathers of sons engaged in more rough and tumble play (RTP), used more achievement language with their sons, and had a stronger neural response to their son's neutral facial expressions in the medial OFC (mOFC). Whereas the mOFC response to happy faces was negatively related to RTP, the mOFC response to neutral faces was positively related to RTP, specifically for fathers of boys. These results indicate that real-world paternal behavior and brain function differ as a function of child gender. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  7. Language effects in second-language learners: A longitudinal electrophysiological study of spanish classroom learning.

    Science.gov (United States)

    Soskey, Laura; Holcomb, Phillip J; Midgley, Katherine J

    2016-09-01

    How do the neural mechanisms involved in word recognition evolve over the course of word learning in adult learners of a new second language? The current study sought to closely track language effects, which are differences in electrophysiological indices of word processing between one's native and second languages, in beginning university learners over the course of a single semester of learning. Monolingual L1 English-speakers enrolled in introductory Spanish were first trained on a list of 228 Spanish words chosen from the vocabulary to be learned in class. Behavioral data from the training session and the following experimental sessions spaced over the course of the semester showed expected learning effects. In the three laboratory sessions participants read words in three lists (English, Spanish and mixed) while performing a go/no-go lexical decision task in which event-related potentials (ERPs) were recorded. As observed in previous studies there were ERP language effects with larger N400s to native than second language words. Importantly, this difference declined over the course of L2 learning with N400 amplitude increasing for new second language words. These results suggest that even over a single semester of learning that new second language words are rapidly incorporated into the word recognition system and begin to take on lexical and semantic properties similar to native language words. Moreover, the results suggest that electrophysiological measures can be used as sensitive measures for tracking the acquisition of new linguistic knowledge. Copyright © 2016 Elsevier B.V. All rights reserved.

  8. Organic chemistry as a language and the implications of chemical linguistics for structural and retrosynthetic analyses.

    Science.gov (United States)

    Cadeddu, Andrea; Wylie, Elizabeth K; Jurczak, Janusz; Wampler-Doty, Matthew; Grzybowski, Bartosz A

    2014-07-28

    Methods of computational linguistics are used to demonstrate that a natural language such as English and organic chemistry have the same structure in terms of the frequency of, respectively, text fragments and molecular fragments. This quantitative correspondence suggests that it is possible to extend the methods of computational corpus linguistics to the analysis of organic molecules. It is shown that within organic molecules bonds that have highest information content are the ones that 1) define repeat/symmetry subunits and 2) in asymmetric molecules, define the loci of potential retrosynthetic disconnections. Linguistics-based analysis appears well-suited to the analysis of complex structural and reactivity patterns within organic molecules. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Programming languages for synthetic biology.

    Science.gov (United States)

    Umesh, P; Naveen, F; Rao, Chanchala Uma Maheswara; Nair, Achuthsankar S

    2010-12-01

    In the backdrop of accelerated efforts for creating synthetic organisms, the nature and scope of an ideal programming language for scripting synthetic organism in-silico has been receiving increasing attention. A few programming languages for synthetic biology capable of defining, constructing, networking, editing and delivering genome scale models of cellular processes have been recently attempted. All these represent important points in a spectrum of possibilities. This paper introduces Kera, a state of the art programming language for synthetic biology which is arguably ahead of similar languages or tools such as GEC, Antimony and GenoCAD. Kera is a full-fledged object oriented programming language which is tempered by biopart rule library named Samhita which captures the knowledge regarding the interaction of genome components and catalytic molecules. Prominent feature of the language are demonstrated through a toy example and the road map for the future development of Kera is also presented.

  10. Prediction of octanol-water partition coefficients of organic compounds by multiple linear regression, partial least squares, and artificial neural network.

    Science.gov (United States)

    Golmohammadi, Hassan

    2009-11-30

    A quantitative structure-property relationship (QSPR) study was performed to develop models those relate the structure of 141 organic compounds to their octanol-water partition coefficients (log P(o/w)). A genetic algorithm was applied as a variable selection tool. Modeling of log P(o/w) of these compounds as a function of theoretically derived descriptors was established by multiple linear regression (MLR), partial least squares (PLS), and artificial neural network (ANN). The best selected descriptors that appear in the models are: atomic charge weighted partial positively charged surface area (PPSA-3), fractional atomic charge weighted partial positive surface area (FPSA-3), minimum atomic partial charge (Qmin), molecular volume (MV), total dipole moment of molecule (mu), maximum antibonding contribution of a molecule orbital in the molecule (MAC), and maximum free valency of a C atom in the molecule (MFV). The result obtained showed the ability of developed artificial neural network to prediction of partition coefficients of organic compounds. Also, the results revealed the superiority of ANN over the MLR and PLS models. Copyright 2009 Wiley Periodicals, Inc.

  11. Dutch-Cantonese Bilinguals Show Segmental Processing during Sinitic Language Production

    Directory of Open Access Journals (Sweden)

    Kalinka Timmer

    2017-07-01

    Full Text Available This study addressed the debate on the primacy of syllable vs. segment (i.e., phoneme as a functional unit of phonological encoding in syllabic languages by investigating both behavioral and neural responses of Dutch-Cantonese (DC bilinguals in a color-object picture naming task. Specifically, we investigated whether DC bilinguals exhibit the phonemic processing strategy, evident in monolingual Dutch speakers, during planning of their Cantonese speech production. Participants named the color of colored line-drawings in Cantonese faster when color and object matched in the first segment than when they were mismatched (e.g., 藍駱駝, /laam4/ /lok3to4/, “blue camel;” 紅饑駝, /hung4/ /lok3to4/, “red camel”. This is in contrast to previous studies in Sinitic languages that did not reveal such phoneme-only facilitation. Phonemic overlap also modulated the event-related potentials (ERPs in the 125–175, 200–300, and 300–400 ms time windows, suggesting earlier ERP modulations than in previous studies with monolingual Sinitic speakers or unbalanced Sinitic-Germanic bilinguals. Conjointly, our results suggest that, while the syllable may be considered the primary unit of phonological encoding in Sinitic languages, the phoneme can serve as the primary unit of phonological encoding, both behaviorally and neurally, for DC bilinguals. The presence/absence of a segment onset effect in Sinitic languages may be related to the proficiency in the Germanic language of bilinguals.

  12. Programming Languages RESONAN

    Indian Academy of Sciences (India)

    Introduction. Programming languages for computers are developed with the ... detailed algorithm to solve a problem is the starting point and it is expressed as ... All modern programming .... which precisely specify the 'words' of the language, and how they may .... network within an organization using protocols and providing.

  13. Many languages, one classroom teaching dual and English language learners

    CERN Document Server

    Nemeth, Karen

    2009-01-01

    Even the most experienced teacher can feel a bit unsure about meeting the unique needs of children from different language backgrounds. Many Languages, One Classroom applies the latest information about best practices to all aspects of a preschool program. Organized by interest areas and times of the day, you'll find everything you need to open the doors of literacy and learning for English language learners during dramatic play, outdoor play, reading, science, blocks, and circle time.

  14. PSYCHOLOGICAL AND PEDAGOGICAL FACTORS OF STUDENT SELF-STUDY ORGANIZATION ON ACQUIRING FOREIGN LANGUAGE COMMUNICATIVE COMPETENCE

    Directory of Open Access Journals (Sweden)

    Iryna Zadorozhna

    2016-12-01

    Full Text Available Psychological and pedagogical prerequisites of student self-study organization on acquiring foreign language communicative competence have been defined and characterized. It has been proved that self-study effectiveness depends on self-regulation and motivation. The latter is amplified by creating a situation of development, modelling personally meaningful learning context aimed at creating a real product; collaborative learning, incorporating modern technologies, using problematic tasks, regular feedback, professionally-oriented learning. On the basis of scientific literature analysis it has been concluded that self-regulation of future foreign language teachers has the following structure: defining objectives, modelling meaningful conditions, action programming, results evaluation, program correction. Ways of developing self-control, self-evaluation and self-correction have been analyzed in the article. Pedagogical preconditions of effective self-study are the following: student knowledge of efficient methods and procedures of foreign language learning; selection of procedures and strategies adequate to the defined goals; an appropriate level of student information culture; ability to manage time and control results; timely correction on the basis of current control and self-control.

  15. Dynamic decomposition of spatiotemporal neural signals.

    Directory of Open Access Journals (Sweden)

    Luca Ambrogioni

    2017-05-01

    Full Text Available Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals.

  16. Perceived Conventionality in Co-speech Gestures Involves the Fronto-Temporal Language Network

    Directory of Open Access Journals (Sweden)

    Dhana Wolf

    2017-11-01

    Full Text Available Face-to-face communication is multimodal; it encompasses spoken words, facial expressions, gaze, and co-speech gestures. In contrast to linguistic symbols (e.g., spoken words or signs in sign language relying on mostly explicit conventions, gestures vary in their degree of conventionality. Bodily signs may have a general accepted or conventionalized meaning (e.g., a head shake or less so (e.g., self-grooming. We hypothesized that subjective perception of conventionality in co-speech gestures relies on the classical language network, i.e., the left hemispheric inferior frontal gyrus (IFG, Broca's area and the posterior superior temporal gyrus (pSTG, Wernicke's area and studied 36 subjects watching video-recorded story retellings during a behavioral and an functional magnetic resonance imaging (fMRI experiment. It is well documented that neural correlates of such naturalistic videos emerge as intersubject covariance (ISC in fMRI even without involving a stimulus (model-free analysis. The subjects attended either to perceived conventionality or to a control condition (any hand movements or gesture-speech relations. Such tasks modulate ISC in contributing neural structures and thus we studied ISC changes to task demands in language networks. Indeed, the conventionality task significantly increased covariance of the button press time series and neuronal synchronization in the left IFG over the comparison with other tasks. In the left IFG, synchronous activity was observed during the conventionality task only. In contrast, the left pSTG exhibited correlated activation patterns during all conditions with an increase in the conventionality task at the trend level only. Conceivably, the left IFG can be considered a core region for the processing of perceived conventionality in co-speech gestures similar to spoken language. In general, the interpretation of conventionalized signs may rely on neural mechanisms that engage during language comprehension.

  17. "Language Learning" Roundtable: Memory and Second Language Acquisition 2012, Hong Kong

    Science.gov (United States)

    Wen, Zhisheng; McNeill, Arthur; Mota, Mailce Borges

    2014-01-01

    Organized under the auspices of the "Language Learning" Roundtable Conference Grant (2012), this seminar aimed to provide an interactive forum for a group of second language acquisition (SLA) researchers with particular interests in cognitive linguistics and psycholinguistics to discuss key theoretical and methodological issues in the…

  18. The oscillopathic nature of language deficits in autism: from genes to language evolution

    Directory of Open Access Journals (Sweden)

    Antonio eBenítez-Burraco

    2016-03-01

    Full Text Available Autism spectrum disorders (ASD are pervasive neurodevelopmental disorders involving a number of deficits to linguistic cognition. The gap between genetics and the pathophysiology of ASD remains open, in particular regarding its distinctive linguistic profile. The goal of this paper is to attempt to bridge this gap, focusing on how the autistic brain processes language, particularly through the perspective of brain rhythms. Due to the phenomenon of pleiotropy, which may take some decades to overcome, we believe that studies of brain rhythms, which are not faced with problems of this scale, may constitute a more tractable route to interpreting language deficits in ASD and eventually other neurocognitive disorders. Building on recent attempts to link neural oscillations to certain computational primitives of language, we show that interpreting language deficits in ASD as oscillopathic traits is a potentially fruitful way to construct successful endophenotypes of this condition. Additionally, we will show that candidate genes for ASD are overrepresented among the genes that played a role in the evolution of language. These genes include (and are related to genes involved in brain rhythmicity. We hope that the type of steps taken here will additionally lead to a better understanding of the comorbidity, heterogeneity, and variability of ASD, and may help achieve a better treatment of the affected populations.

  19. Precursors to language: Social cognition and pragmatic inference in primates.

    Science.gov (United States)

    Seyfarth, Robert M; Cheney, Dorothy L

    2017-02-01

    Despite their differences, human language and the vocal communication of nonhuman primates share many features. Both constitute forms of coordinated activity, rely on many shared neural mechanisms, and involve discrete, combinatorial cognition that includes rich pragmatic inference. These common features suggest that during evolution the ancestors of all modern primates faced similar social problems and responded with similar systems of communication and cognition. When language later evolved from this common foundation, many of its distinctive features were already present.

  20. Neural correlates of rhyming vs. lexical and semantic fluency.

    Science.gov (United States)

    Kircher, Tilo; Nagels, Arne; Kirner-Veselinovic, André; Krach, Sören

    2011-05-19

    Rhyming words, as in songs or poems, is a universal feature of human language across all ages. In the present fMRI study a novel overt rhyming task was applied to determine the neural correlates of rhyme production. Fifteen right-handed healthy male volunteers participated in this verbal fluency study. Participants were instructed to overtly articulate as many words as possible either to a given initial letter (LVF) or to a semantic category (SVF). During the rhyming verbal fluency task (RVF), participants had to generate words that rhymed with pseudoword stimuli. On-line overt verbal responses were audiotaped in order to correct the imaging results for the number of generated words. Fewer words were generated in the rhyming compared to both the lexical and the semantic condition. On a neural level, all language tasks activated a language network encompassing the left inferior frontal gyrus, the middle and superior temporal gyri as well as the contralateral right cerebellum. Rhyming verbal fluency compared to both lexical and semantic verbal fluency demonstrated significantly stronger activation of left inferior parietal region. Generating novel rhyme words seems to be mainly mediated by the left inferior parietal lobe, a region previously found to be associated with meta-phonological as well as sub-lexical linguistic processes. Copyright © 2011 Elsevier B.V. All rights reserved.

  1. 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.

  2. 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.

  3. Plain language and organisational challenges

    DEFF Research Database (Denmark)

    Pedersen, Karsten

    2014-01-01

    Changing the language in an organization is a major organizational change. In this article, I discuss some of the organizational challenges for one specific language change implementation, taking the stance that language change must be treated as any other organizational change for it to have an ...

  4. Why Are There Developmental Stages in Language Learning? A Developmental Robotics Model of Language Development.

    Science.gov (United States)

    Morse, Anthony F; Cangelosi, Angelo

    2017-02-01

    Most theories of learning would predict a gradual acquisition and refinement of skills as learning progresses, and while some highlight exponential growth, this fails to explain why natural cognitive development typically progresses in stages. Models that do span multiple developmental stages typically have parameters to "switch" between stages. We argue that by taking an embodied view, the interaction between learning mechanisms, the resulting behavior of the agent, and the opportunities for learning that the environment provides can account for the stage-wise development of cognitive abilities. We summarize work relevant to this hypothesis and suggest two simple mechanisms that account for some developmental transitions: neural readiness focuses on changes in the neural substrate resulting from ongoing learning, and perceptual readiness focuses on the perceptual requirements for learning new tasks. Previous work has demonstrated these mechanisms in replications of a wide variety of infant language experiments, spanning multiple developmental stages. Here we piece this work together as a single model of ongoing learning with no parameter changes at all. The model, an instance of the Epigenetic Robotics Architecture (Morse et al 2010) embodied on the iCub humanoid robot, exhibits ongoing multi-stage development while learning pre-linguistic and then basic language skills. Copyright © 2016 Cognitive Science Society, Inc.

  5. How right is left? Handedness modulates neural responses during morphosyntactic processing.

    Science.gov (United States)

    Grey, Sarah; Tanner, Darren; van Hell, Janet G

    2017-08-15

    Most neurocognitive models of language processing generally assume population-wide homogeneity in the neural mechanisms used during language comprehension, yet individual differences are known to influence these neural mechanisms. In this study, we focus on handedness as an individual difference hypothesized to affect language comprehension. Left-handers and right-handers with a left-handed blood relative, or familial sinistrals, are hypothesized to process language differently than right-handers with no left-handed relatives (Hancock and Bever, 2013; Ullman, 2004). Yet, left-handers are often excluded from neurocognitive language research, and familial sinistrality in right-handers is often not taken into account. In the current study we used event-related potentials to test morphosyntactic processing in three groups that differed in their handedness profiles: left-handers (LH), right-handers with a left-handed blood relative (RH FS+), and right-handers with no reported left-handed blood relative (RH FS-; both right-handed groups were previously tested by Tanner and Van Hell, 2014). Results indicated that the RH FS- group showed only P600 responses during morphosyntactic processing whereas the LH and RH FS+ groups showed biphasic N400-P600 patterns. N400s in LH and RH FS+ groups are consistent with theories that associate left-handedness (self or familial) with increased reliance on lexical/semantic mechanisms during language processing. Inspection of individual-level results illustrated that variability in RH FS- individuals' morphosyntactic processing was remarkably low: most individuals were P600-dominant. In contrast, LH and RH FS+ individuals showed marked variability in brain responses, which was similar for both groups: half of individuals were N400-dominant and half were P600-dominant. Our findings have implications for neurocognitive models of language that have been largely formulated around data from only right-handers without accounting for familial

  6. HAL/S language specification

    Science.gov (United States)

    Newbold, P. M.

    1974-01-01

    A programming language for the flight software of the NASA space shuttle program was developed and identified as HAL/S. The language is intended to satisfy virtually all of the flight software requirements of the space shuttle. The language incorporates a wide range of features, including applications-oriented data types and organizations, real time control mechanisms, and constructs for systems programming tasks.

  7. 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.

  8. Complex-valued neural networks advances and applications

    CERN Document Server

    Hirose, Akira

    2013-01-01

    Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ultrasonic waves as well as quantum waves, namely, electron and

  9. Computational modeling of spiking neural network with learning rules from STDP and intrinsic plasticity

    Science.gov (United States)

    Li, Xiumin; Wang, Wei; Xue, Fangzheng; Song, Yongduan

    2018-02-01

    Recently there has been continuously increasing interest in building up computational models of spiking neural networks (SNN), such as the Liquid State Machine (LSM). The biologically inspired self-organized neural networks with neural plasticity can enhance the capability of computational performance, with the characteristic features of dynamical memory and recurrent connection cycles which distinguish them from the more widely used feedforward neural networks. Despite a variety of computational models for brain-like learning and information processing have been proposed, the modeling of self-organized neural networks with multi-neural plasticity is still an important open challenge. The main difficulties lie in the interplay among different forms of neural plasticity rules and understanding how structures and dynamics of neural networks shape the computational performance. In this paper, we propose a novel approach to develop the models of LSM with a biologically inspired self-organizing network based on two neural plasticity learning rules. The connectivity among excitatory neurons is adapted by spike-timing-dependent plasticity (STDP) learning; meanwhile, the degrees of neuronal excitability are regulated to maintain a moderate average activity level by another learning rule: intrinsic plasticity (IP). Our study shows that LSM with STDP+IP performs better than LSM with a random SNN or SNN obtained by STDP alone. The noticeable improvement with the proposed method is due to the better reflected competition among different neurons in the developed SNN model, as well as the more effectively encoded and processed relevant dynamic information with its learning and self-organizing mechanism. This result gives insights to the optimization of computational models of spiking neural networks with neural plasticity.

  10. Transcranial magnetic stimulation: language function.

    Science.gov (United States)

    Epstein, C M

    1998-07-01

    Studies of language using transcranial magnetic stimulation (TMS) have focused both on identification of language areas and on elucidation of function. TMS may result in either inhibition or facilitation of language processes and may operate directly at a presumptive site of language cortex or indirectly through intracortical networks. TMS has been used to create reversible "temporary lesions," similar to those produced by Wada tests and direct cortical electrical stimulation, in cerebral cortical areas subserving language function. Rapid-rate TMS over the left inferior frontal region blocks speech output in most subjects. However, the results are not those predicted from classic models of language organization. Speech arrest is obtained most easily over facial motor cortex, and true aphasia is rare, whereas right hemisphere or bilateral lateralization is unexpectedly prominent. A clinical role for these techniques is not yet fully established. Interfering with language comprehension and verbal memory is currently more difficult than blocking speech output, but numerous TMS studies have demonstrated facilitation of language-related tasks, including oral word association, story recall, digit span, and picture naming. Conversely, speech output also facilitates motor responses to TMS in the dominant hemisphere. Such new and often-unexpected findings may provide important insights into the organization of language.

  11. Sex Differences in Neural Processing of Language among Children

    Science.gov (United States)

    Burman, Douglas D.; Bitan, Tali; Booth, James R.

    2008-01-01

    Why females generally perform better on language tasks than males is unknown. Sex differences were here identified in children (ages 9-15) across two linguistic tasks for words presented in two modalities. Bilateral activation in the inferior frontal and superior temporal gyri and activation in the left fusiform gyrus of girls was greater than in…

  12. Character Recognition Using Genetically Trained Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Diniz, C.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-10-01

    Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfid recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the

  13. Understanding the role of speech production in reading: Evidence for a print-to-speech neural network using graphical analysis.

    Science.gov (United States)

    Cummine, Jacqueline; Cribben, Ivor; Luu, Connie; Kim, Esther; Bahktiari, Reyhaneh; Georgiou, George; Boliek, Carol A

    2016-05-01

    The neural circuitry associated with language processing is complex and dynamic. Graphical models are useful for studying complex neural networks as this method provides information about unique connectivity between regions within the context of the entire network of interest. Here, the authors explored the neural networks during covert reading to determine the role of feedforward and feedback loops in covert speech production. Brain activity of skilled adult readers was assessed in real word and pseudoword reading tasks with functional MRI (fMRI). The authors provide evidence for activity coherence in the feedforward system (inferior frontal gyrus-supplementary motor area) during real word reading and in the feedback system (supramarginal gyrus-precentral gyrus) during pseudoword reading. Graphical models provided evidence of an extensive, highly connected, neural network when individuals read real words that relied on coordination of the feedforward system. In contrast, when individuals read pseudowords the authors found a limited/restricted network that relied on coordination of the feedback system. Together, these results underscore the importance of considering multiple pathways and articulatory loops during language tasks and provide evidence for a print-to-speech neural network. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  14. Language-dependent changes in pitch-relevant neural activity in the auditory cortex reflect differential weighting of temporal attributes of pitch contours

    Science.gov (United States)

    Krishnan, Ananthanarayan; Gandour, Jackson T.; Xu, Yi; Suresh, Chandan H.

    2016-01-01

    There remains a gap in our knowledge base about neural representation of pitch attributes that occur between onset and offset of dynamic, curvilinear pitch contours. The aim is to evaluate how language experience shapes processing of pitch contours as reflected in the amplitude of cortical pitch-specific response components. Responses were elicited from three nonspeech, bidirectional (falling-rising) pitch contours representative of Mandarin Tone 2 varying in location of the turning point with fixed onset and offset. At the frontocentral Fz electrode site, Na–Pb and Pb–Nb amplitude of the Chinese group was larger than the English group for pitch contours exhibiting later location of the turning point relative to the one with the earliest location. Chinese listeners’ amplitude was also greater than that of English in response to those same pitch contours with later turning points. At lateral temporal sites (T7/T8), Na–Pb amplitude was larger in Chinese listeners relative to English over the right temporal site. In addition, Pb–Nb amplitude of the Chinese group showed a rightward asymmetry. The pitch contour with its turning point located about halfway of total duration evoked a rightward asymmetry regardless of group. These findings suggest that neural mechanisms processing pitch in the right auditory cortex reflect experience-dependent modulation of sensitivity to weighted integration of changes in acceleration rates of rising and falling sections and the location of the turning point. PMID:28713201

  15. Effects of different language and tDCS interventions in PPA and their neural correlates

    Directory of Open Access Journals (Sweden)

    Kyrana Tsapkini

    2015-05-01

    Results: First, we replicated our previous results obtained with fewer participants: all improved in both tDCS and sham conditions on trained items. Generalization of treatment on untrained items was significant only in tDCS condition. Therapy gains lasted longer in tDCS condition as well. Second, preliminary analyses of rs-fMRI show changes of functional connectivity between written language areas in the tDCS and sham conditions. Conclusions: tDCS represents an increasingly valuable treatment option in language rehabilitation even in neurodegeneration. Late intervention is as beneficial as early intervention but improvement seems more dramatic in early cases. Different possibilities are discussed: tDCS may indeed change the course of the disease, i.e., it may slow down the rate of decline or, language improvement due to tDCS (or delay in language deterioration due to the course of the disease may hold the spread of decline in other cognitive functions, thus, early interventions appear more beneficial. The correlation between functional connectivity and language production outcomes is expected to shed light on how tDCS works in the brains of people with a neurodegenerative disease. Implications of functional connectivity changes between language areas involved in the targeted language function will inform further interventions.

  16. Workshop on Language Student Attrition

    National Research Council Canada - National Science Library

    Whelan, Bree

    2001-01-01

    Seventy individuals from Government agencies (military and civilian), academia, and contractor organizations attended all or parts of a Workshop on student Attrition held at the Defense Language Institute Foreign Language Center (DLIFLC...

  17. Artificial neural network with self-organizing mapping for reactor stability monitoring

    International Nuclear Information System (INIS)

    Okumura, Motofumi; Tsuji, Masashi; Shimazu, Yoichiro

    2009-01-01

    In boiling water reactor (BWR) stability monitoring, damping ratio has been used as a stability index. A method for estimating the damping ratio by applying Principal Component Analysis (PCA) to neutron detector signals measured with local power range monitors (LPRMs) had been developed; in this method, measured fluctuating signal is decomposed into some independent components and the signal components directly related to stability are extracted among them to determine the damping ratio. For online monitoring, it is necessary to select stability related signal components efficiently. The self-organizing map (SOM) is one of the artificial neural networks (ANNs) and has the characteristics such that online learning is possible without supervised learning within a relatively short time. In the present study, the SOM was applied to extract the relevant signal components more quickly and more accurately, and the availability was confirmed through the feasibility study. For realizing online stability monitoring only with ANNs, another type of ANN that performs online processing of PCA was combined with SOM. And stability monitoring performance was investigated. (author)

  18. Left hemisphere EEG coherence in infancy predicts infant declarative pointing and preschool epistemic language.

    Science.gov (United States)

    Kühn-Popp, N; Kristen, S; Paulus, M; Meinhardt, J; Sodian, B

    2016-01-01

    Pointing plays a central role in preverbal communication. While imperative pointing aims at influencing another person's behavior, declarative gestures serve to convey epistemic information and to share interest in an object. Further, the latter are hypothesized to be a precursor ability of epistemic language. So far, little is known about their underlying brain maturation processes. Therefore, the present study investigated the relation between brain maturation processes and the production of imperative and declarative motives as well as epistemic language in N = 32 infants. EEG coherence scores were measured at 14 months, imperative and declarative point production at 15 months and epistemic language at 48 months. Results of correlational analyses suggest distinct behavioral and neural patterns for imperative and declarative pointing, with declarative pointing being associated with the maturation of the left hemisphere. Further, EEG coherence measures of the left hemisphere at 14 months and declarative pointing at 15 months are related to individual differences in epistemic language skills at 48 months, independently of child IQ. In regression analyses, coherence measures of the left hemisphere prove to be the most important predictor of epistemic language skills. Thus, neural processes of the left hemisphere seem particularly relevant to social communication.

  19. The neural organization of perception in chess experts.

    Science.gov (United States)

    Krawczyk, Daniel C; Boggan, Amy L; McClelland, M Michelle; Bartlett, James C

    2011-07-20

    The human visual system responds to expertise, and it has been suggested that regions that process faces also process other objects of expertise including chess boards by experts. We tested whether chess and face processing overlap in brain activity using fMRI. Chess experts and novices exhibited face selective areas, but these regions showed no selectivity to chess configurations relative to other stimuli. We next compared neural responses to chess and to scrambled chess displays to isolate areas relevant to expertise. Areas within the posterior cingulate, orbitofrontal cortex, and right temporal cortex were active in this comparison in experts over novices. We also compared chess and face responses within the posterior cingulate and found this area responsive to chess only in experts. These findings indicate that the configurations in chess are not strongly processed by face-selective regions that are selective for faces in individuals who have expertise in both domains. Further, the area most consistently involved in chess did not show overlap with faces. Overall, these results suggest that expert visual processing may be similar at the level of recognition, but need not show the same neural correlates. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  20. Rhythmic Effects of Syntax Processing in Music and Language.

    Science.gov (United States)

    Jung, Harim; Sontag, Samuel; Park, YeBin S; Loui, Psyche

    2015-01-01

    Music and language are human cognitive and neural functions that share many structural similarities. Past theories posit a sharing of neural resources between syntax processing in music and language (Patel, 2003), and a dynamic attention network that governs general temporal processing (Large and Jones, 1999). Both make predictions about music and language processing over time. Experiment 1 of this study investigates the relationship between rhythmic expectancy and musical and linguistic syntax in a reading time paradigm. Stimuli (adapted from Slevc et al., 2009) were sentences broken down into segments; each sentence segment was paired with a musical chord and presented at a fixed inter-onset interval. Linguistic syntax violations appeared in a garden-path design. During the critical region of the garden-path sentence, i.e., the particular segment in which the syntactic unexpectedness was processed, expectancy violations for language, music, and rhythm were each independently manipulated: musical expectation was manipulated by presenting out-of-key chords and rhythmic expectancy was manipulated by perturbing the fixed inter-onset interval such that the sentence segments and musical chords appeared either early or late. Reading times were recorded for each sentence segment and compared for linguistic, musical, and rhythmic expectancy. Results showed main effects of rhythmic expectancy and linguistic syntax expectancy on reading time. There was also an effect of rhythm on the interaction between musical and linguistic syntax: effects of violations in musical and linguistic syntax showed significant interaction only during rhythmically expected trials. To test the effects of our experimental design on rhythmic and linguistic expectancies, independently of musical syntax, Experiment 2 used the same experimental paradigm, but the musical factor was eliminated-linguistic stimuli were simply presented silently, and rhythmic expectancy was manipulated at the critical

  1. Insights into neural crest development from studies of avian embryos

    OpenAIRE

    Gandhi, Shashank; Bronner, Marianne E.

    2018-01-01

    The neural crest is a multipotent and highly migratory cell type that contributes to many of the defining features of vertebrates, including the skeleton of the head and most of the peripheral nervous system. 150 years after the discovery of the neural crest, avian embryos remain one of the most important model organisms for studying neural crest development. In this review, we describe aspects of neural crest induction, migration and axial level differences, highlighting what is known about ...

  2. Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.

    Science.gov (United States)

    Hu, Peijun; Wu, Fa; Peng, Jialin; Bao, Yuanyuan; Chen, Feng; Kong, Dexing

    2017-03-01

    Multi-organ segmentation from CT images is an essential step for computer-aided diagnosis and surgery planning. However, manual delineation of the organs by radiologists is tedious, time-consuming and poorly reproducible. Therefore, we propose a fully automatic method for the segmentation of multiple organs from three-dimensional abdominal CT images. The proposed method employs deep fully convolutional neural networks (CNNs) for organ detection and segmentation, which is further refined by a time-implicit multi-phase evolution method. Firstly, a 3D CNN is trained to automatically localize and delineate the organs of interest with a probability prediction map. The learned probability map provides both subject-specific spatial priors and initialization for subsequent fine segmentation. Then, for the refinement of the multi-organ segmentation, image intensity models, probability priors as well as a disjoint region constraint are incorporated into an unified energy functional. Finally, a novel time-implicit multi-phase level-set algorithm is utilized to efficiently optimize the proposed energy functional model. Our method has been evaluated on 140 abdominal CT scans for the segmentation of four organs (liver, spleen and both kidneys). With respect to the ground truth, average Dice overlap ratios for the liver, spleen and both kidneys are 96.0, 94.2 and 95.4%, respectively, and average symmetric surface distance is less than 1.3 mm for all the segmented organs. The computation time for a CT volume is 125 s in average. The achieved accuracy compares well to state-of-the-art methods with much higher efficiency. A fully automatic method for multi-organ segmentation from abdominal CT images was developed and evaluated. The results demonstrated its potential in clinical usage with high effectiveness, robustness and efficiency.

  3. 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

  4. Applications of self-organizing neural networks in virtual screening and diversity selection.

    Science.gov (United States)

    Selzer, Paul; Ertl, Peter

    2006-01-01

    Artificial neural networks provide a powerful technique for the analysis and modeling of nonlinear relationships between molecular structures and pharmacological activity. Many network types, including Kohonen and counterpropagation, also provide an intuitive method for the visual assessment of correspondence between the input and output data. This work shows how a combination of neural networks and radial distribution function molecular descriptors can be applied in various areas of industrial pharmaceutical research. These applications include the prediction of biological activity, the selection of screening candidates (cherry picking), and the extraction of representative subsets from large compound collections such as combinatorial libraries. The methods described have also been implemented as an easy-to-use Web tool, allowing chemists to perform interactive neural network experiments on the Novartis intranet.

  5. Prediction of air-to-blood partition coefficients of volatile organic compounds using genetic algorithm and artificial neural network

    International Nuclear Information System (INIS)

    Konoz, Elahe; Golmohammadi, Hassan

    2008-01-01

    An artificial neural network (ANN) was constructed and trained for the prediction of air-to-blood partition coefficients of volatile organic compounds. The inputs of this neural network are theoretically derived descriptors that were chosen by genetic algorithm (GA) and multiple linear regression (MLR) features selection techniques. These descriptors are: R maximal autocorrelation of lag 1 weighted by atomic Sanderson electronegativities (R1E+), electron density on the most negative atom in molecule (EDNA), maximum partial charge for C atom (MXPCC), surface weighted charge partial surface area (WNSA1), fractional charge partial surface area (FNSA2) and atomic charge weighted partial positive surface area (PPSA3). The standard errors of training, test and validation sets for the ANN model are 0.095, 0.148 and 0.120, respectively. Result obtained showed that nonlinear model can simulate the relationship between structural descriptors and the partition coefficients of the molecules in data set accurately

  6. Neural networks for perception human and machine perception

    CERN Document Server

    Wechsler, Harry

    1991-01-01

    Neural Networks for Perception, Volume 1: Human and Machine Perception focuses on models for understanding human perception in terms of distributed computation and examples of PDP models for machine perception. This book addresses both theoretical and practical issues related to the feasibility of both explaining human perception and implementing machine perception in terms of neural network models. The book is organized into two parts. The first part focuses on human perception. Topics on network model ofobject recognition in human vision, the self-organization of functional architecture in t

  7. Language distance and tree reconstruction

    International Nuclear Information System (INIS)

    Petroni, Filippo; Serva, Maurizio

    2008-01-01

    Languages evolve over time according to a process in which reproduction, mutation and extinction are all possible. This is very similar to haploid evolution for asexual organisms and for the mitochondrial DNA of complex ones. Exploiting this similarity, it is possible, in principle, to verify hypotheses concerning the relationship among languages and to reconstruct their family tree. The key point is the definition of the distances among pairs of languages in analogy with the genetic distances among pairs of organisms. Distances can be evaluated by comparing grammar and/or vocabulary, but while it is difficult, if not impossible, to quantify grammar distance, it is possible to measure a distance from vocabulary differences. The method used by glottochronology computes distances from the percentage of shared 'cognates', which are words with a common historical origin. The weak point of this method is that subjective judgment plays a significant role. Here we define the distance of two languages by considering a renormalized edit distance among words with the same meaning and averaging over the two hundred words contained in a Swadesh list. In our approach the vocabulary of a language is the analogue of DNA for organisms. The advantage is that we avoid subjectivity and, furthermore, reproducibility of results is guaranteed. We apply our method to the Indo-European and the Austronesian groups, considering, in both cases, fifty different languages. The two trees obtained are, in many respects, similar to those found by glottochronologists, with some important differences as regards the positions of a few languages. In order to support these different results we separately analyze the structure of the distances of these languages with respect to all the others

  8. Language distance and tree reconstruction

    Science.gov (United States)

    Petroni, Filippo; Serva, Maurizio

    2008-08-01

    Languages evolve over time according to a process in which reproduction, mutation and extinction are all possible. This is very similar to haploid evolution for asexual organisms and for the mitochondrial DNA of complex ones. Exploiting this similarity, it is possible, in principle, to verify hypotheses concerning the relationship among languages and to reconstruct their family tree. The key point is the definition of the distances among pairs of languages in analogy with the genetic distances among pairs of organisms. Distances can be evaluated by comparing grammar and/or vocabulary, but while it is difficult, if not impossible, to quantify grammar distance, it is possible to measure a distance from vocabulary differences. The method used by glottochronology computes distances from the percentage of shared 'cognates', which are words with a common historical origin. The weak point of this method is that subjective judgment plays a significant role. Here we define the distance of two languages by considering a renormalized edit distance among words with the same meaning and averaging over the two hundred words contained in a Swadesh list. In our approach the vocabulary of a language is the analogue of DNA for organisms. The advantage is that we avoid subjectivity and, furthermore, reproducibility of results is guaranteed. We apply our method to the Indo-European and the Austronesian groups, considering, in both cases, fifty different languages. The two trees obtained are, in many respects, similar to those found by glottochronologists, with some important differences as regards the positions of a few languages. In order to support these different results we separately analyze the structure of the distances of these languages with respect to all the others.

  9. Neural representations of emotion are organized around abstract event features.

    Science.gov (United States)

    Skerry, Amy E; Saxe, Rebecca

    2015-08-03

    Research on emotion attribution has tended to focus on the perception of overt expressions of at most five or six basic emotions. However, our ability to identify others' emotional states is not limited to perception of these canonical expressions. Instead, we make fine-grained inferences about what others feel based on the situations they encounter, relying on knowledge of the eliciting conditions for different emotions. In the present research, we provide convergent behavioral and neural evidence concerning the representations underlying these concepts. First, we find that patterns of activity in mentalizing regions contain information about subtle emotional distinctions conveyed through verbal descriptions of eliciting situations. Second, we identify a space of abstract situation features that well captures the emotion discriminations subjects make behaviorally and show that this feature space outperforms competing models in capturing the similarity space of neural patterns in these regions. Together, the data suggest that our knowledge of others' emotions is abstract and high dimensional, that brain regions selective for mental state reasoning support relatively subtle distinctions between emotion concepts, and that the neural representations in these regions are not reducible to more primitive affective dimensions such as valence and arousal. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Gestures Enhance Foreign Language Learning

    Directory of Open Access Journals (Sweden)

    Manuela Macedonia

    2012-11-01

    Full Text Available Language and gesture are highly interdependent systems that reciprocally influence each other. For example, performing a gesture when learning a word or a phrase enhances its retrieval compared to pure verbal learning. Although the enhancing effects of co-speech gestures on memory are known to be robust, the underlying neural mechanisms are still unclear. Here, we summarize the results of behavioral and neuroscientific studies. They indicate that the neural representation of words consists of complex multimodal networks connecting perception and motor acts that occur during learning. In this context, gestures can reinforce the sensorimotor representation of a word or a phrase, making it resistant to decay. Also, gestures can favor embodiment of abstract words by creating it from scratch. Thus, we propose the use of gesture as a facilitating educational tool that integrates body and mind.

  11. Ways of making-sense: Local gamma synchronization reveals differences between semantic processing induced by music and language.

    Science.gov (United States)

    Barraza, Paulo; Chavez, Mario; Rodríguez, Eugenio

    2016-01-01

    Similar to linguistic stimuli, music can also prime the meaning of a subsequent word. However, it is so far unknown what is the brain dynamics underlying the semantic priming effect induced by music, and its relation to language. To elucidate these issues, we compare the brain oscillatory response to visual words that have been semantically primed either by a musical excerpt or by an auditory sentence. We found that semantic violation between music-word pairs triggers a classical ERP N400, and induces a sustained increase of long-distance theta phase synchrony, along with a transient increase of local gamma activity. Similar results were observed after linguistic semantic violation except for gamma activity, which increased after semantic congruence between sentence-word pairs. Our findings indicate that local gamma activity is a neural marker that signals different ways of semantic processing between music and language, revealing the dynamic and self-organized nature of the semantic processing. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. 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.

  13. Neural correlates of pragmatic language comprehension in autism spectrum disorders

    NARCIS (Netherlands)

    Tesink, C.M.J.Y.; Buitelaar, J.K.; Petersson, K.M.; Gaag, R.J. van der; Kan, C.C.; Tendolkar, I.; Hagoort, P.

    2009-01-01

    Difficulties with pragmatic aspects of communication are universal across individuals with autism spectrum disorders (ASDs). Here we focused on an aspect of pragmatic language comprehension that is relevant to social interaction in daily life: the integration of speaker characteristics inferred from

  14. Neural correlates of pragmatic language comprehension in autism spectrum disorders.

    NARCIS (Netherlands)

    Tesink, C.M.J.Y.; Buitelaar, J.K.; Petersson, K.M.; Gaag, R.J. van der; Kan, C.C.; Tendolkar, I.; Hagoort, P.

    2009-01-01

    Difficulties with pragmatic aspects of communication are universal across individuals with autism spectrum disorders (ASDs). Here we focused on an aspect of pragmatic language comprehension that is relevant to social interaction in daily life: the integration of speaker characteristics inferred from

  15. Neural correlates and network connectivity underlying narrative production and comprehension: a combined fMRI and PET study.

    Science.gov (United States)

    AbdulSabur, Nuria Y; Xu, Yisheng; Liu, Siyuan; Chow, Ho Ming; Baxter, Miranda; Carson, Jessica; Braun, Allen R

    2014-08-01

    The neural correlates of narrative production and comprehension remain poorly understood. Here, using positron emission tomography (PET), functional magnetic resonance imaging (fMRI), contrast and functional network connectivity analyses we comprehensively characterize the neural mechanisms underlying these complex behaviors. Eighteen healthy subjects told and listened to fictional stories during scanning. In addition to traditional language areas (e.g., left inferior frontal and posterior middle temporal gyri), both narrative production and comprehension engaged regions associated with mentalizing and situation model construction (e.g., dorsomedial prefrontal cortex, precuneus and inferior parietal lobules) as well as neocortical premotor areas, such as the pre-supplementary motor area and left dorsal premotor cortex. Narrative comprehension alone showed marked bilaterality, activating right hemisphere homologs of perisylvian language areas. Narrative production remained predominantly left lateralized, uniquely activating executive and motor-related regions essential to language formulation and articulation. Connectivity analyses revealed strong associations between language areas and the superior and middle temporal gyri during both tasks. However, only during storytelling were these same language-related regions connected to cortical and subcortical motor regions. In contrast, during story comprehension alone, they were strongly linked to regions supporting mentalizing. Thus, when employed in a more complex, ecologically-valid context, language production and comprehension show both overlapping and idiosyncratic patterns of activation and functional connectivity. Importantly, in each case the language system is integrated with regions that support other cognitive and sensorimotor domains. Copyright © 2014. Published by Elsevier Ltd.

  16. Processing lexical semantic and syntactic information in first and second language: fMRI evidence from German and Russian.

    Science.gov (United States)

    Rüschemeyer, Shirley-Ann; Fiebach, Christian J; Kempe, Vera; Friederici, Angela D

    2005-06-01

    We introduce two experiments that explored syntactic and semantic processing of spoken sentences by native and non-native speakers. In the first experiment, the neural substrates corresponding to detection of syntactic and semantic violations were determined in native speakers of two typologically different languages using functional magnetic resonance imaging (fMRI). The results show that the underlying neural response of participants to stimuli across different native languages is quite similar. In the second experiment, we investigated how non-native speakers of a language process the same stimuli presented in the first experiment. First, the results show a more similar pattern of increased activation between native and non-native speakers in response to semantic violations than to syntactic violations. Second, the non-native speakers were observed to employ specific portions of the frontotemporal language network differently from those employed by native speakers. These regions included the inferior frontal gyrus (IFG), superior temporal gyrus (STG), and subcortical structures of the basal ganglia.

  17. Computational Investigations of Multiword Chunks in Language Learning.

    Science.gov (United States)

    McCauley, Stewart M; Christiansen, Morten H

    2017-07-01

    Second-language learners rarely arrive at native proficiency in a number of linguistic domains, including morphological and syntactic processing. Previous approaches to understanding the different outcomes of first- versus second-language learning have focused on cognitive and neural factors. In contrast, we explore the possibility that children and adults may rely on different linguistic units throughout the course of language learning, with specific focus on the granularity of those units. Following recent psycholinguistic evidence for the role of multiword chunks in online language processing, we explore the hypothesis that children rely more heavily on multiword units in language learning than do adults learning a second language. To this end, we take an initial step toward using large-scale, corpus-based computational modeling as a tool for exploring the granularity of speakers' linguistic units. Employing a computational model of language learning, the Chunk-Based Learner, we compare the usefulness of chunk-based knowledge in accounting for the speech of second-language learners versus children and adults speaking their first language. Our findings suggest that while multiword units are likely to play a role in second-language learning, adults may learn less useful chunks, rely on them to a lesser extent, and arrive at them through different means than children learning a first language. Copyright © 2017 Cognitive Science Society, Inc.

  18. Does EFL Readers' Lexical and Grammatical Knowledge Predict Their Reading Ability? Insights from a Perceptron Artificial Neural Network Study

    Science.gov (United States)

    Aryadoust, Vahid; Baghaei, Purya

    2016-01-01

    This study aims to examine the relationship between reading comprehension and lexical and grammatical knowledge among English as a foreign language students by using an Artificial Neural Network (ANN). There were 825 test takers administered both a second-language reading test and a set of psychometrically validated grammar and vocabulary tests.…

  19. Rethinking clinical language mapping approaches: discordant receptive and expressive hemispheric language dominance in epilepsy surgery candidates.

    Science.gov (United States)

    Gage, Nicole M; Eliashiv, Dawn S; Isenberg, Anna L; Fillmore, Paul T; Kurelowech, Lacey; Quint, Patti J; Chung, Jeffrey M; Otis, Shirley M

    2011-06-01

    Neuroimaging studies have shed light on cortical language organization, with findings implicating the left and right temporal lobes in speech processing converging to a left-dominant pattern. Findings highlight the fact that the state of theoretical language knowledge is ahead of current clinical language mapping methods, motivating a rethinking of these approaches. The authors used magnetoencephalography and multiple tasks in seven candidates for resective epilepsy surgery to investigate language organization. The authors scanned 12 control subjects to investigate the time course of bilateral receptive speech processes. Laterality indices were calculated for left and right hemisphere late fields ∼150 to 400 milliseconds. The authors report that (1) in healthy adults, speech processes activated superior temporal regions bilaterally converging to a left-dominant pattern, (2) in four of six patients, this was reversed, with bilateral processing converging to a right-dominant pattern, and (3) in three of four of these patients, receptive and expressive language processes were laterally discordant. Results provide evidence that receptive and expressive language may have divergent hemispheric dominance. Right-sided receptive language dominance in epilepsy patients emphasizes the need to assess both receptive and expressive language. Findings indicate that it is critical to use multiple tasks tapping separable aspects of language function to provide sensitive and specific estimates of language localization in surgical patients.

  20. Risk factors, organ weight deviation and associated anomalies in neural tube defects: A prospective fetal and perinatal autopsy series

    Directory of Open Access Journals (Sweden)

    Asaranti Kar

    2015-01-01

    Full Text Available Introduction: Neural tube defects (NTD are a group of serious birth defects occurring due to defective closure of neural tube during embryonic development. It comprises of anencephaly, encephalocele and spina bifida. We conducted this prospective fetal autopsy series to study the rate and distribution of NTD, analyze the reproductive factors and risk factors, note any associated anomalies and evaluate the organ weights and their deviation from normal. Materials and Methods: This was a prospective study done over a period of 6 years from August, 2007 to July, 2013. All cases of NTDs delivered as abortion, still born and live born were included. The reproductive and risk factors like age, parity, multiple births, previous miscarriage, obesity, diabetes mellitus, socioeconomic status and use of folic acid during pregnancy were collected.Autopsy was performed according to Virchow′s technique. Detail external and internal examination were carried out to detect any associated anomalies. Gross and microscopic examination of organs were done. Results: Out of 210 cases of fetal and perinatal autopsy done, 72 (34.28% had NTD constituting 49 cases of anencephaly, 16 spina bifida and 7 cases of encephalocele. The mothers in these cases predominantly were within 25-29 years (P = 0.02 and primy (P = 0.01. Female sex was more commonly affected than males (M:F = 25:47, P = 0.0005 There was no history of folate use in majority of cases. Organ weight deviations were >2 standard deviation low in most of the cases. Most common associated anomalies were adrenal hypoplasia and thymic hyperplasia. Conclusion: The authors have made an attempt to study NTD cases in respect to maternal reproductive and risk factors and their association with NTD along with the organ weight deviation and associated anomalies. This so far in our knowledge is an innovative study which was not found in literature even after extensive search.

  1. Technologies for Language Assessment.

    Science.gov (United States)

    Burstein, Jill; And Others

    1996-01-01

    Reviews current and developing technology uses that are relevant to language assessment and discusses examples of recent linguistic applications from the laboratory at the Educational Testing Service. The processes of language test development are described and the functions they serve from the perspective of a large testing organization are…

  2. The Case for Interactionism in Language Processing.

    Science.gov (United States)

    1987-04-28

    D-AIBB 133 THE CASE FOR INTERACTIONISM IN LANGUAGE PROCESSING(U) 1/1 CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF PSYCHOLOGY J L MCCLELLAND, 28 APR 87...Interaction in Language Processing The Case for Interactionism in Language Processing James L. McClelland Department of Psychology Carnegie-Mellon...REPORT NUMBER(S) 5 MONITORING ORGANIZATION REPORT NUMBER(S) Technical Report 0NR-87-1 6a NAME OF PERFORMING ORGANIZATION 6b OFFICE SYMBOL 7a. NAME OF

  3. The role of the episodic buffer in working memory for language processing.

    Science.gov (United States)

    Rudner, Mary; Rönnberg, Jerker

    2008-03-01

    A body of work has accumulated to show that the cognitive process of binding information from different mnemonic and sensory sources as well as in different linguistic modalities can be fractionated from general executive functions in working memory both functionally and neurally. This process has been defined in terms of the episodic buffer (Baddeley in Trends Cogn Sci 4(11):417-423, 2000). This paper considers behavioural, neuropsychological and neuroimaging data that elucidate the role of the episodic buffer in language processing. We argue that the episodic buffer seems to be truly multimodal in function and that while formation of unitary multidimensional representations in the episodic buffer seems to engage posterior neural networks, maintenance of such representations is supported by frontal networks. Although, the episodic buffer is not necessarily supported by executive processes and seems to be supported by different neural networks, it may operate in tandem with the central executive during effortful language processing. There is also evidence to suggest engagement of the phonological loop during buffer processing. The hippocampus seems to play a role in formation but not maintenance of representations in the episodic buffer of working memory.

  4. Language-universal sensory deficits in developmental dyslexia: English, Spanish, and Chinese.

    Science.gov (United States)

    Goswami, Usha; Wang, H-L Sharon; Cruz, Alicia; Fosker, Tim; Mead, Natasha; Huss, Martina

    2011-02-01

    Studies in sensory neuroscience reveal the critical importance of accurate sensory perception for cognitive development. There is considerable debate concerning the possible sensory correlates of phonological processing, the primary cognitive risk factor for developmental dyslexia. Across languages, children with dyslexia have a specific difficulty with the neural representation of the phonological structure of speech. The identification of a robust sensory marker of phonological difficulties would enable early identification of risk for developmental dyslexia and early targeted intervention. Here, we explore whether phonological processing difficulties are associated with difficulties in processing acoustic cues to speech rhythm. Speech rhythm is used across languages by infants to segment the speech stream into words and syllables. Early difficulties in perceiving auditory sensory cues to speech rhythm and prosody could lead developmentally to impairments in phonology. We compared matched samples of children with and without dyslexia, learning three very different spoken and written languages, English, Spanish, and Chinese. The key sensory cue measured was rate of onset of the amplitude envelope (rise time), known to be critical for the rhythmic timing of speech. Despite phonological and orthographic differences, for each language, rise time sensitivity was a significant predictor of phonological awareness, and rise time was the only consistent predictor of reading acquisition. The data support a language-universal theory of the neural basis of developmental dyslexia on the basis of rhythmic perception and syllable segmentation. They also suggest that novel remediation strategies on the basis of rhythm and music may offer benefits for phonological and linguistic development.

  5. 1/f neural noise and electrophysiological indices of contextual prediction in aging.

    Science.gov (United States)

    Dave, S; Brothers, T A; Swaab, T Y

    2018-07-15

    Prediction of upcoming words during reading has been suggested to enhance the efficiency of discourse processing. Emerging models have postulated that predictive mechanisms require synchronous firing of neural networks, but to date, this relationship has been investigated primarily through oscillatory activity in narrow frequency bands. A recently-developed measure proposed to reflect broadband neural activity - and thereby synchronous neuronal firing - is 1/f neural noise extracted from EEG spectral power. Previous research has indicated that this measure of 1/f neural noise changes across the lifespan, and these neural changes predict age-related behavioral impairments in visual working memory. Using a cross-sectional sample of young and older adults, we examined age-related changes in 1/f neural noise and whether this measure predicted ERP correlates of successful lexical prediction during discourse comprehension. 1/f neural noise across two different language tasks revealed high within-subject correlations, indicating that this measure can provide a reliable index of individualized patterns of neural activation. In addition to age, 1/f noise was a significant predictor of N400 effects of successful lexical prediction; however, noise did not mediate age-related declines in other ERP effects. We discuss broader implications of these findings for theories of predictive processing, as well as potential applications of 1/f noise across research populations. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Optimization of multilayer neural network parameters for speaker recognition

    Science.gov (United States)

    Tovarek, Jaromir; Partila, Pavol; Rozhon, Jan; Voznak, Miroslav; Skapa, Jan; Uhrin, Dominik; Chmelikova, Zdenka

    2016-05-01

    This article discusses the impact of multilayer neural network parameters for speaker identification. The main task of speaker identification is to find a specific person in the known set of speakers. It means that the voice of an unknown speaker (wanted person) belongs to a group of reference speakers from the voice database. One of the requests was to develop the text-independent system, which means to classify wanted person regardless of content and language. Multilayer neural network has been used for speaker identification in this research. Artificial neural network (ANN) needs to set parameters like activation function of neurons, steepness of activation functions, learning rate, the maximum number of iterations and a number of neurons in the hidden and output layers. ANN accuracy and validation time are directly influenced by the parameter settings. Different roles require different settings. Identification accuracy and ANN validation time were evaluated with the same input data but different parameter settings. The goal was to find parameters for the neural network with the highest precision and shortest validation time. Input data of neural networks are a Mel-frequency cepstral coefficients (MFCC). These parameters describe the properties of the vocal tract. Audio samples were recorded for all speakers in a laboratory environment. Training, testing and validation data set were split into 70, 15 and 15 %. The result of the research described in this article is different parameter setting for the multilayer neural network for four speakers.

  7. 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.

  8. Language comprehension warps the mirror neuron system

    Directory of Open Access Journals (Sweden)

    Noah eZarr

    2013-12-01

    Full Text Available Is the mirror neuron system (MNS used in language understanding? According to embodied accounts of language comprehension, understanding sentences describing actions makes use of neural mechanisms of action control, including the MNS. Consequently, repeatedly comprehending sentences describing similar actions should induce adaptation of the MNS thereby warping its use in other cognitive processes such as action recognition and prediction. To test this prediction, participants read blocks of multiple sentences where each sentence in the block described transfer of objects in a direction away or toward the reader. Following each block, adaptation was measured by having participants predict the end-point of videotaped actions. The adapting sentences disrupted prediction of actions in the same direction, but a only for videos of biological motion, and b only when the effector implied by the language (e.g., the hand matched the videos. These findings are signatures of the mirror neuron system.

  9. Language comprehension warps the mirror neuron system.

    Science.gov (United States)

    Zarr, Noah; Ferguson, Ryan; Glenberg, Arthur M

    2013-01-01

    Is the mirror neuron system (MNS) used in language understanding? According to embodied accounts of language comprehension, understanding sentences describing actions makes use of neural mechanisms of action control, including the MNS. Consequently, repeatedly comprehending sentences describing similar actions should induce adaptation of the MNS thereby warping its use in other cognitive processes such as action recognition and prediction. To test this prediction, participants read blocks of multiple sentences where each sentence in the block described transfer of objects in a direction away or toward the reader. Following each block, adaptation was measured by having participants predict the end-point of videotaped actions. The adapting sentences disrupted prediction of actions in the same direction, but (a) only for videos of biological motion, and (b) only when the effector implied by the language (e.g., the hand) matched the videos. These findings are signatures of the MNS.

  10. Organization of the sleep-related neural systems in the brain of the minke whale (Balaenoptera acutorostrata).

    Science.gov (United States)

    Dell, Leigh-Anne; Karlsson, Karl Ae; Patzke, Nina; Spocter, Muhammad A; Siegel, Jerome M; Manger, Paul R

    2016-07-01

    The current study analyzed the nuclear organization of the neural systems related to the control and regulation of sleep and wake in the basal forebrain, diencephalon, midbrain, and pons of the minke whale, a mysticete cetacean. While odontocete cetaceans sleep in an unusual manner, with unihemispheric slow wave sleep (USWS) and suppressed REM sleep, it is unclear whether the mysticete whales show a similar sleep pattern. Previously, we detailed a range of features in the odontocete brain that appear to be related to odontocete-type sleep, and here present our analysis of these features in the minke whale brain. All neural elements involved in sleep regulation and control found in bihemispheric sleeping mammals and the harbor porpoise were present in the minke whale, with no specific nuclei being absent, and no novel nuclei being present. This qualitative similarity relates to the cholinergic, noradrenergic, serotonergic and orexinergic systems, and the GABAergic elements of these nuclei. Quantitative analysis revealed that the numbers of pontine cholinergic (274,242) and noradrenergic (203,686) neurons, and hypothalamic orexinergic neurons (277,604), are markedly higher than other large-brained bihemispheric sleeping mammals. Small telencephalic commissures (anterior, corpus callosum, and hippocampal), an enlarged posterior commissure, supernumerary pontine cholinergic and noradrenergic cells, and an enlarged peripheral division of the dorsal raphe nuclear complex of the minke whale, all indicate that the suite of neural characteristics thought to be involved in the control of USWS and the suppression of REM in the odontocete cetaceans are present in the minke whale. J. Comp. Neurol. 524:2018-2035, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

  11. Social Interaction in Infants' Learning of Second-Language Phonetics: An Exploration of Brain-Behavior Relations.

    Science.gov (United States)

    Conboy, Barbara T; Brooks, Rechele; Meltzoff, Andrew N; Kuhl, Patricia K

    2015-01-01

    Infants learn phonetic information from a second language with live-person presentations, but not television or audio-only recordings. To understand the role of social interaction in learning a second language, we examined infants' joint attention with live, Spanish-speaking tutors and used a neural measure of phonetic learning. Infants' eye-gaze behaviors during Spanish sessions at 9.5-10.5 months of age predicted second-language phonetic learning, assessed by an event-related potential measure of Spanish phoneme discrimination at 11 months. These data suggest a powerful role for social interaction at the earliest stages of learning a new language.

  12. Speaking Two Languages Enhances an Auditory but Not a Visual Neural Marker of Cognitive Inhibition

    Directory of Open Access Journals (Sweden)

    Mercedes Fernandez

    2014-09-01

    Full Text Available The purpose of the present study was to replicate and extend our original findings of enhanced neural inhibitory control in bilinguals. We compared English monolinguals to Spanish/English bilinguals on a non-linguistic, auditory Go/NoGo task while recording event-related brain potentials. New to this study was the visual Go/NoGo task, which we included to investigate whether enhanced neural inhibition in bilinguals extends from the auditory to the visual modality. Results confirmed our original findings and revealed greater inhibition in bilinguals compared to monolinguals. As predicted, compared to monolinguals, bilinguals showed increased N2 amplitude during the auditory NoGo trials, which required inhibitory control, but no differences during the Go trials, which required a behavioral response and no inhibition. Interestingly, during the visual Go/NoGo task, event related brain potentials did not distinguish the two groups, and behavioral responses were similar between the groups regardless of task modality. Thus, only auditory trials that required inhibitory control revealed between-group differences indicative of greater neural inhibition in bilinguals. These results show that experience-dependent neural changes associated with bilingualism are specific to the auditory modality and that the N2 event-related brain potential is a sensitive marker of this plasticity.

  13. Spanish-Language Community-Based Mental Health Treatment Programs, Policy-Required Language-Assistance Programming, and Mental Health Treatment Access Among Spanish-Speaking Clients

    Science.gov (United States)

    McClellan, Sean R.

    2013-01-01

    Objectives. We investigated the extent to which implementing language assistance programming through contracting with community-based organizations improved the accessibility of mental health care under Medi-Cal (California’s Medicaid program) for Spanish-speaking persons with limited English proficiency, and whether it reduced language-based treatment access disparities. Methods. Using a time series nonequivalent control group design, we studied county-level penetration of language assistance programming over 10 years (1997–2006) for Spanish-speaking persons with limited English proficiency covered under Medi-Cal. We used linear regression with county fixed effects to control for ongoing trends and other influences. Results. When county mental health plans contracted with community-based organizations, those implementing language assistance programming increased penetration rates of Spanish-language mental health services under Medi-Cal more than other plans (0.28 percentage points, a 25% increase on average; P language-related disparities. Conclusions. Mental health treatment programs operated by community-based organizations may have moderately improved access after implementing required language assistance programming, but the programming did not reduce entrenched disparities in the accessibility of mental health services. PMID:23865663

  14. Spanish-language community-based mental health treatment programs, policy-required language-assistance programming, and mental health treatment access among Spanish-speaking clients.

    Science.gov (United States)

    Snowden, Lonnie R; McClellan, Sean R

    2013-09-01

    We investigated the extent to which implementing language assistance programming through contracting with community-based organizations improved the accessibility of mental health care under Medi-Cal (California's Medicaid program) for Spanish-speaking persons with limited English proficiency, and whether it reduced language-based treatment access disparities. Using a time series nonequivalent control group design, we studied county-level penetration of language assistance programming over 10 years (1997-2006) for Spanish-speaking persons with limited English proficiency covered under Medi-Cal. We used linear regression with county fixed effects to control for ongoing trends and other influences. When county mental health plans contracted with community-based organizations, those implementing language assistance programming increased penetration rates of Spanish-language mental health services under Medi-Cal more than other plans (0.28 percentage points, a 25% increase on average; P language-related disparities. Mental health treatment programs operated by community-based organizations may have moderately improved access after implementing required language assistance programming, but the programming did not reduce entrenched disparities in the accessibility of mental health services.

  15. High school music classes enhance the neural processing of speech

    Directory of Open Access Journals (Sweden)

    Adam eTierney

    2013-12-01

    Full Text Available Should music be a priority in public education? One argument for teaching music in school is that private music instruction relates to enhanced language abilities and neural function. However, the directionality of this relationship is unclear and it is unknown whether school-based music training can produce these enhancements. Here we show that two years of group music classes in high school enhance the subcortical encoding of speech. To tease apart the relationships between music and neural function, we tested high school students participating in either music or fitness-based training. These groups were matched at the onset of training on neural timing, reading ability, and IQ. Auditory brainstem responses were collected to a synthesized speech sound presented in background noise. After 2 years of training, the subcortical responses of the music training group were earlier than at pretraining, while the neural timing of students in the fitness training group was unchanged. These results represent the strongest evidence to date that in-school music education can cause enhanced speech encoding. The neural benefits of musical training are, therefore, not limited to expensive private instruction early in childhood but can be elicited by cost-effective group instruction during adolescence.

  16. Dynamic concision for three-dimensional reconstruction of human organ built with virtual reality modelling language (VRML)*

    Science.gov (United States)

    Yu, Zheng-yang; Zheng, Shu-sen; Chen, Lei-ting; He, Xiao-qian; Wang, Jian-jun

    2005-01-01

    This research studies the process of 3D reconstruction and dynamic concision based on 2D medical digital images using virtual reality modelling language (VRML) and JavaScript language, with a focus on how to realize the dynamic concision of 3D medical model with script node and sensor node in VRML. The 3D reconstruction and concision of body internal organs can be built with such high quality that they are better than those obtained from the traditional methods. With the function of dynamic concision, the VRML browser can offer better windows for man-computer interaction in real-time environment than ever before. 3D reconstruction and dynamic concision with VRML can be used to meet the requirement for the medical observation of 3D reconstruction and have a promising prospect in the fields of medical imaging. PMID:15973760

  17. Identifying Emotions on the Basis of Neural Activation.

    Science.gov (United States)

    Kassam, Karim S; Markey, Amanda R; Cherkassky, Vladimir L; Loewenstein, George; Just, Marcel Adam

    2013-01-01

    We attempt to determine the discriminability and organization of neural activation corresponding to the experience of specific emotions. Method actors were asked to self-induce nine emotional states (anger, disgust, envy, fear, happiness, lust, pride, sadness, and shame) while in an fMRI scanner. Using a Gaussian Naïve Bayes pooled variance classifier, we demonstrate the ability to identify specific emotions experienced by an individual at well over chance accuracy on the basis of: 1) neural activation of the same individual in other trials, 2) neural activation of other individuals who experienced similar trials, and 3) neural activation of the same individual to a qualitatively different type of emotion induction. Factor analysis identified valence, arousal, sociality, and lust as dimensions underlying the activation patterns. These results suggest a structure for neural representations of emotion and inform theories of emotional processing.

  18. Proposal of a model of mammalian neural induction

    Science.gov (United States)

    Levine, Ariel J.; Brivanlou, Ali H.

    2009-01-01

    How does the vertebrate embryo make a nervous system? This complex question has been at the center of developmental biology for many years. The earliest step in this process – the induction of neural tissue – is intimately linked to patterning of the entire early embryo, and the molecular and embryological basis these processes are beginning to emerge. Here, we analyze classic and cutting-edge findings on neural induction in the mouse. We find that data from genetics, tissue explants, tissue grafting, and molecular marker expression support a coherent framework for mammalian neural induction. In this model, the gastrula organizer of the mouse embryo inhibits BMP signaling to allow neural tissue to form as a default fate – in the absence of instructive signals. The first neural tissue induced is anterior and subsequent neural tissue is posteriorized to form the midbrain, hindbrain, and spinal cord. The anterior visceral endoderm protects the pre-specified anterior neural fate from similar posteriorization, allowing formation of forebrain. This model is very similar to the default model of neural induction in the frog, thus bridging the evolutionary gap between amphibians and mammals. PMID:17585896

  19. Atypical language laterality is associated with large-scale disruption of network integration in children with intractable focal epilepsy.

    Science.gov (United States)

    Ibrahim, George M; Morgan, Benjamin R; Doesburg, Sam M; Taylor, Margot J; Pang, Elizabeth W; Donner, Elizabeth; Go, Cristina Y; Rutka, James T; Snead, O Carter

    2015-04-01

    Epilepsy is associated with disruption of integration in distributed networks, together with altered localization for functions such as expressive language. The relation between atypical network connectivity and altered localization is unknown. In the current study we tested whether atypical expressive language laterality was associated with the alteration of large-scale network integration in children with medically-intractable localization-related epilepsy (LRE). Twenty-three right-handed children (age range 8-17) with medically-intractable LRE performed a verb generation task in fMRI. Language network activation was identified and the Laterality index (LI) was calculated within the pars triangularis and pars opercularis. Resting-state data from the same cohort were subjected to independent component analysis. Dual regression was used to identify associations between resting-state integration and LI values. Higher positive values of the LI, indicating typical language localization were associated with stronger functional integration of various networks including the default mode network (DMN). The normally symmetric resting-state networks showed a pattern of lateralized connectivity mirroring that of language function. The association between atypical language localization and network integration implies a widespread disruption of neural network development. These findings may inform the interpretation of localization studies by providing novel insights into reorganization of neural networks in epilepsy. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. 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…

  1. Delaying Onset of Dementia: Are Two Languages Enough?

    Directory of Open Access Journals (Sweden)

    Morris Freedman

    2014-01-01

    Full Text Available There is an emerging literature suggesting that speaking two or more languages may significantly delay the onset of dementia. Although the mechanisms are unknown, it has been suggested that these may involve cognitive reserve, a concept that has been associated with factors such as higher levels of education, occupational status, social networks, and physical exercise. In the case of bilingualism, cognitive reserve may involve reorganization and strengthening of neural networks that enhance executive control. We review evidence for protective effects of bilingualism from a multicultural perspective involving studies in Toronto and Montreal, Canada, and Hyderabad, India. Reports from Toronto and Hyderabad showed a significant effect of speaking two or more languages in delaying onset of Alzheimer’s disease by up to 5 years, whereas the Montreal study showed a significant protective effect of speaking at least four languages and a protective effect of speaking at least two languages in immigrants. Although there were differences in results across studies, a common theme was the significant effect of language use history as one of the factors in determining the onset of Alzheimer’s disease. Moreover, the Hyderabad study extended the findings to frontotemporal dementia and vascular dementia.

  2. Delaying onset of dementia: are two languages enough?

    Science.gov (United States)

    Freedman, Morris; Alladi, Suvarna; Chertkow, Howard; Bialystok, Ellen; Craik, Fergus I M; Phillips, Natalie A; Duggirala, Vasanta; Raju, Surampudi Bapi; Bak, Thomas H

    2014-01-01

    There is an emerging literature suggesting that speaking two or more languages may significantly delay the onset of dementia. Although the mechanisms are unknown, it has been suggested that these may involve cognitive reserve, a concept that has been associated with factors such as higher levels of education, occupational status, social networks, and physical exercise. In the case of bilingualism, cognitive reserve may involve reorganization and strengthening of neural networks that enhance executive control. We review evidence for protective effects of bilingualism from a multicultural perspective involving studies in Toronto and Montreal, Canada, and Hyderabad, India. Reports from Toronto and Hyderabad showed a significant effect of speaking two or more languages in delaying onset of Alzheimer's disease by up to 5 years, whereas the Montreal study showed a significant protective effect of speaking at least four languages and a protective effect of speaking at least two languages in immigrants. Although there were differences in results across studies, a common theme was the significant effect of language use history as one of the factors in determining the onset of Alzheimer's disease. Moreover, the Hyderabad study extended the findings to frontotemporal dementia and vascular dementia.

  3. Modelling the phonotactic structure of natural language words with simple recurrent networks

    NARCIS (Netherlands)

    Stoianov, [No Value; Nerbonne, J; Bouma, H; Coppen, PA; vanHalteren, H; Teunissen, L

    1998-01-01

    Simple Recurrent Networks (SRN) are Neural Network (connectionist) models able to process natural language. Phonotactics concerns the order of symbols in words. We continued an earlier unsuccessful trial to model the phonotactics of Dutch words with SRNs. In order to overcome the previously reported

  4. Distorted Character Recognition Via An Associative Neural Network

    Science.gov (United States)

    Messner, Richard A.; Szu, Harold H.

    1987-03-01

    The purpose of this paper is two-fold. First, it is intended to provide some preliminary results of a character recognition scheme which has foundations in on-going neural network architecture modeling, and secondly, to apply some of the neural network results in a real application area where thirty years of effort has had little effect on providing the machine an ability to recognize distorted objects within the same object class. It is the author's belief that the time is ripe to start applying in ernest the results of over twenty years of effort in neural modeling to some of the more difficult problems which seem so hard to solve by conventional means. The character recognition scheme proposed utilizes a preprocessing stage which performs a 2-dimensional Walsh transform of an input cartesian image field, then sequency filters this spectrum into three feature bands. Various features are then extracted and organized into three sets of feature vectors. These vector patterns that are stored and recalled associatively. Two possible associative neural memory models are proposed for further investigation. The first being an outer-product linear matrix associative memory with a threshold function controlling the strength of the output pattern (similar to Kohonen's crosscorrelation approach [1]). The second approach is based upon a modified version of Grossberg's neural architecture [2] which provides better self-organizing properties due to its adaptive nature. Preliminary results of the sequency filtering and feature extraction preprocessing stage and discussion about the use of the proposed neural architectures is included.

  5. Encouraging Second Language Use in Cooperative Learning Groups

    Directory of Open Access Journals (Sweden)

    George M Jacobs

    2013-11-01

    Full Text Available This article presents, explains and organizes ideas for promoting students’ use of their second language (this term includes foreign language when they work together in cooperative learning groups. The first part of the article reviews arguments as to whether students of second languages should be encouraged to use their second language with classmates when doing group activities. These arguments are discussed with reference to Second Language Acquisition (SLA theory. Practical issues are also explored. Next, the majority of the article presents ideas on how to promote second language use during peer interaction. Twenty-nine of these ideas are explained. The ideas are organized into five categories: a role for the L1; understanding the issue; creating a conducive climate; providing language support; and the task. It is recommended that teachers use ideas from the literature on cooperative learning when they ask students to interact.

  6. Mapping Language Problems in the Brain

    Science.gov (United States)

    ... issue Health Capsule 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 ...

  7. Music enrichment programs improve the neural encoding of speech in at-risk children.

    Science.gov (United States)

    Kraus, Nina; Slater, Jessica; Thompson, Elaine C; Hornickel, Jane; Strait, Dana L; Nicol, Trent; White-Schwoch, Travis

    2014-09-03

    Musicians are often reported to have enhanced neurophysiological functions, especially in the auditory system. Musical training is thought to improve nervous system function by focusing attention on meaningful acoustic cues, and these improvements in auditory processing cascade to language and cognitive skills. Correlational studies have reported musician enhancements in a variety of populations across the life span. In light of these reports, educators are considering the potential for co-curricular music programs to provide auditory-cognitive enrichment to children during critical developmental years. To date, however, no studies have evaluated biological changes following participation in existing, successful music education programs. We used a randomized control design to investigate whether community music participation induces a tangible change in auditory processing. The community music training was a longstanding and successful program that provides free music instruction to children from underserved backgrounds who stand at high risk for learning and social problems. Children who completed 2 years of music training had a stronger neurophysiological distinction of stop consonants, a neural mechanism linked to reading and language skills. One year of training was insufficient to elicit changes in nervous system function; beyond 1 year, however, greater amounts of instrumental music training were associated with larger gains in neural processing. We therefore provide the first direct evidence that community music programs enhance the neural processing of speech in at-risk children, suggesting that active and repeated engagement with sound changes neural function. Copyright © 2014 the authors 0270-6474/14/3411913-06$15.00/0.

  8. A NEW RECOGNITION TECHNIQUE NAMED SOMP BASED ON PALMPRINT USING NEURAL NETWORK BASED SELF ORGANIZING MAPS

    Directory of Open Access Journals (Sweden)

    A. S. Raja

    2012-08-01

    Full Text Available The word biometrics refers to the use of physiological or biological characteristics of human to recognize and verify the identity of an individual. Palmprint has become a new class of human biometrics for passive identification with uniqueness and stability. This is considered to be reliable due to the lack of expressions and the lesser effect of aging. In this manuscript a new Palmprint based biometric system based on neural networks self organizing maps (SOM is presented. The method is named as SOMP. The paper shows that the proposed SOMP method improves the performance and robustness of recognition. The proposed method is applied to a variety of datasets and the results are shown.

  9. Levels of processing and language modality specificity in working memory.

    Science.gov (United States)

    Rudner, Mary; Karlsson, Thomas; Gunnarsson, Johan; Rönnberg, Jerker

    2013-03-01

    Neural networks underpinning working memory demonstrate sign language specific components possibly related to differences in temporary storage mechanisms. A processing approach to memory systems suggests that the organisation of memory storage is related to type of memory processing as well. In the present study, we investigated for the first time semantic, phonological and orthographic processing in working memory for sign- and speech-based language. During fMRI we administered a picture-based 2-back working memory task with Semantic, Phonological, Orthographic and Baseline conditions to 11 deaf signers and 20 hearing non-signers. Behavioural data showed poorer and slower performance for both groups in Phonological and Orthographic conditions than in the Semantic condition, in line with depth-of-processing theory. An exclusive masking procedure revealed distinct sign-specific neural networks supporting working memory components at all three levels of processing. The overall pattern of sign-specific activations may reflect a relative intermodality difference in the relationship between phonology and semantics influencing working memory storage and processing. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. The role of the left inferior parietal lobule in second language learning: An intensive language training fMRI study.

    Science.gov (United States)

    Barbeau, Elise B; Chai, Xiaoqian J; Chen, Jen-Kai; Soles, Jennika; Berken, Jonathan; Baum, Shari; Watkins, Kate E; Klein, Denise

    2017-04-01

    Research to date suggests that second language acquisition results in functional and structural changes in the bilingual brain, however, in what way and how quickly these changes occur remains unclear. To address these questions, we studied fourteen English-speaking monolingual adults enrolled in a 12-week intensive French language-training program in Montreal. Using functional MRI, we investigated the neural changes associated with new language acquisition. The participants were scanned before the start of the immersion program and at the end of the 12 weeks. The fMRI scan aimed to investigate the brain regions recruited in a sentence reading task both in English, their first language (L1), and in French, their second language (L2). For the L1, fMRI patterns did not change from Time 1 to Time 2, while for the L2, the brain response changed between Time 1 and Time 2 in language-related areas. Of note, for the L2, there was higher activation at Time 2 compared to Time 1 in the left inferior parietal lobule (IPL) including the supramarginal gyrus. At Time 2 this higher activation in the IPL correlated with faster L2 reading speed. Moreover, higher activation in the left IPL at Time 1 predicted improvement in L2 reading speed from Time 1 to Time 2. Our results suggest that learning-induced plasticity occurred as early as 12 weeks into immersive second-language training, and that the IPL appears to play a special role in language learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Identifying Emotions on the Basis of Neural Activation.

    Directory of Open Access Journals (Sweden)

    Karim S Kassam

    Full Text Available We attempt to determine the discriminability and organization of neural activation corresponding to the experience of specific emotions. Method actors were asked to self-induce nine emotional states (anger, disgust, envy, fear, happiness, lust, pride, sadness, and shame while in an fMRI scanner. Using a Gaussian Naïve Bayes pooled variance classifier, we demonstrate the ability to identify specific emotions experienced by an individual at well over chance accuracy on the basis of: 1 neural activation of the same individual in other trials, 2 neural activation of other individuals who experienced similar trials, and 3 neural activation of the same individual to a qualitatively different type of emotion induction. Factor analysis identified valence, arousal, sociality, and lust as dimensions underlying the activation patterns. These results suggest a structure for neural representations of emotion and inform theories of emotional processing.

  12. Emotion in languaging: Language and emotion as affective, adaptive and flexible behavior in social interaction

    Directory of Open Access Journals (Sweden)

    Thomas Wiben Jensen

    2014-07-01

    Full Text Available This article argues for a view on languaging as inherently affective. Informed by recent ecological tendencies within cognitive science and distributed language studies a distinction between first order languaging (language as whole-body sense making and second order language (language as system like constraints is put forward. Contrary to common assumptions within linguistics and communication studies separating language-as-a-system from language use (resulting in separations between language vs. body-language and verbal vs. non-verbal communication etc. the first/second order distinction sees language as emanating from behavior making it possible to view emotion and affect as integral parts languaging behavior. Likewise, emotion and affect are studied, not as inner mental states, but as processes of organism-environment interactions. Based on video recordings of interaction between 1 children with special needs, and 2 couple in therapy and the therapist patterns of reciprocal influences between interactants are examined. Through analyzes of affective stance and patterns of inter-affectivity it is exemplified how language and emotion should not be seen as separate phenomena combined in language use, but rather as completely intertwined phenomena in languaging behavior constrained by second order patterns.

  13. An Initial Investigation of the Neural Correlates of Word Processing in Preschoolers With Specific Language Impairment.

    Science.gov (United States)

    Haebig, Eileen; Leonard, Laurence; Usler, Evan; Deevy, Patricia; Weber, Christine

    2018-03-15

    Previous behavioral studies have found deficits in lexical-semantic abilities in children with specific language impairment (SLI), including reduced depth and breadth of word knowledge. This study explored the neural correlates of early emerging familiar word processing in preschoolers with SLI and typical development. Fifteen preschoolers with typical development and 15 preschoolers with SLI were presented with pictures followed after a brief delay by an auditory label that did or did not match. Event-related brain potentials were time locked to the onset of the auditory labels. Children provided verbal judgments of whether the label matched the picture. There were no group differences in the accuracy of identifying when pictures and labels matched or mismatched. Event-related brain potential data revealed that mismatch trials elicited a robust N400 in both groups, with no group differences in mean amplitude or peak latency. However, the typically developing group demonstrated a more robust late positive component, elicited by mismatch trials. These initial findings indicate that lexical-semantic access of early acquired words, indexed by the N400, does not differ between preschoolers with SLI and typical development when highly familiar words are presented in isolation. However, the typically developing group demonstrated a more mature profile of postlexical reanalysis and integration, indexed by an emerging late positive component. The findings lay the necessary groundwork for better understanding processing of newly learned words in children with SLI.

  14. Design of FPGA Based Neural Network Controller for Earth Station Power System

    Directory of Open Access Journals (Sweden)

    Hassen T. Dorrah

    2012-06-01

    Full Text Available Automation of generating hardware description language code from neural networks models can highly decrease time of implementation those networks into a digital devices, thus significant money savings. To implement the neural network into hardware designer, it is required to translate generated model into device structure. VHDL language is used to describe those networks into hardware. VHDL code has been proposed to implement ANNs as well as to present simulation results with floating point arithmetic of the earth station and the satellite power systems using ModelSim PE 6.6 simulator tool. Integration between MATLAB and VHDL is used to save execution time of computation. The results shows that a good agreement between MATLAB and VHDL and a fast/flexible feed forward NN which is capable of dealing with floating point arithmetic operations; minimum number of CLB slices; and good speed of performance. FPGA synthesis results are obtained with view RTL schematic and technology schematic from Xilinix tool. Minimum number of utilized resources is obtained by using Xilinix VERTIX5.

  15. Neural substrates of interactive musical improvisation: an FMRI study of 'trading fours' in jazz.

    Directory of Open Access Journals (Sweden)

    Gabriel F Donnay

    Full Text Available Interactive generative musical performance provides a suitable model for communication because, like natural linguistic discourse, it involves an exchange of ideas that is unpredictable, collaborative, and emergent. Here we show that interactive improvisation between two musicians is characterized by activation of perisylvian language areas linked to processing of syntactic elements in music, including inferior frontal gyrus and posterior superior temporal gyrus, and deactivation of angular gyrus and supramarginal gyrus, brain structures directly implicated in semantic processing of language. These findings support the hypothesis that musical discourse engages language areas of the brain specialized for processing of syntax but in a manner that is not contingent upon semantic processing. Therefore, we argue that neural regions for syntactic processing are not domain-specific for language but instead may be domain-general for communication.

  16. Neural substrates of interactive musical improvisation: an FMRI study of 'trading fours' in jazz.

    Science.gov (United States)

    Donnay, Gabriel F; Rankin, Summer K; Lopez-Gonzalez, Monica; Jiradejvong, Patpong; Limb, Charles J

    2014-01-01

    Interactive generative musical performance provides a suitable model for communication because, like natural linguistic discourse, it involves an exchange of ideas that is unpredictable, collaborative, and emergent. Here we show that interactive improvisation between two musicians is characterized by activation of perisylvian language areas linked to processing of syntactic elements in music, including inferior frontal gyrus and posterior superior temporal gyrus, and deactivation of angular gyrus and supramarginal gyrus, brain structures directly implicated in semantic processing of language. These findings support the hypothesis that musical discourse engages language areas of the brain specialized for processing of syntax but in a manner that is not contingent upon semantic processing. Therefore, we argue that neural regions for syntactic processing are not domain-specific for language but instead may be domain-general for communication.

  17. Twitter and the Welsh Language

    Science.gov (United States)

    Jones, Rhys James; Cunliffe, Daniel; Honeycutt, Zoe R.

    2013-01-01

    The emergence of new domains, such as the Internet, can prove challenging for minority languages. Welsh is a minority, regional language and is considered "vulnerable" by the United Nations Educational, Scientific and Cultural Organization (UNESCO). The Welsh-speaking community appears to have responded positively to the Internet and the…

  18. Batch Policy Gradient Methods for Improving Neural Conversation Models

    OpenAIRE

    Kandasamy, Kirthevasan; Bachrach, Yoram; Tomioka, Ryota; Tarlow, Daniel; Carter, David

    2017-01-01

    We study reinforcement learning of chatbots with recurrent neural network architectures when the rewards are noisy and expensive to obtain. For instance, a chatbot used in automated customer service support can be scored by quality assurance agents, but this process can be expensive, time consuming and noisy. Previous reinforcement learning work for natural language processing uses on-policy updates and/or is designed for on-line learning settings. We demonstrate empirically that such strateg...

  19. Neural network system and methods for analysis of organic materials and structures using spectral data

    Science.gov (United States)

    Meyer, Bernd J.; Sellers, Jeffrey P.; Thomsen, Jan U.

    1993-01-01

    Apparatus and processes for recognizing and identifying materials. Characteristic spectra are obtained for the materials via spectroscopy techniques including nuclear magnetic resonance spectroscopy, infrared absorption analysis, x-ray analysis, mass spectroscopy and gas chromatography. Desired portions of the spectra may be selected and then placed in proper form and format for presentation to a number of input layer neurons in an offline neural network. The network is first trained according to a predetermined training process; it may then be employed to identify particular materials. Such apparatus and processes are particularly useful for recognizing and identifying organic compounds such as complex carbohydrates, whose spectra conventionally require a high level of training and many hours of hard work to identify, and are frequently indistinguishable from one another by human interpretation.

  20. Hybrid computing using a neural network with dynamic external memory.

    Science.gov (United States)

    Graves, Alex; Wayne, Greg; Reynolds, Malcolm; Harley, Tim; Danihelka, Ivo; Grabska-Barwińska, Agnieszka; Colmenarejo, Sergio Gómez; Grefenstette, Edward; Ramalho, Tiago; Agapiou, John; Badia, Adrià Puigdomènech; Hermann, Karl Moritz; Zwols, Yori; Ostrovski, Georg; Cain, Adam; King, Helen; Summerfield, Christopher; Blunsom, Phil; Kavukcuoglu, Koray; Hassabis, Demis

    2016-10-27

    Artificial neural networks are remarkably adept at sensory processing, sequence learning and reinforcement learning, but are limited in their ability to represent variables and data structures and to store data over long timescales, owing to the lack of an external memory. Here we introduce a machine learning model called a differentiable neural computer (DNC), which consists of a neural network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer. Like a conventional computer, it can use its memory to represent and manipulate complex data structures, but, like a neural network, it can learn to do so from data. When trained with supervised learning, we demonstrate that a DNC can successfully answer synthetic questions designed to emulate reasoning and inference problems in natural language. We show that it can learn tasks such as finding the shortest path between specified points and inferring the missing links in randomly generated graphs, and then generalize these tasks to specific graphs such as transport networks and family trees. When trained with reinforcement learning, a DNC can complete a moving blocks puzzle in which changing goals are specified by sequences of symbols. Taken together, our results demonstrate that DNCs have the capacity to solve complex, structured tasks that are inaccessible to neural networks without external read-write memory.

  1. HAL/SM language specification. [programming languages and computer programming for space shuttles

    Science.gov (United States)

    Williams, G. P. W., Jr.; Ross, C.

    1975-01-01

    A programming language is presented for the flight software of the NASA Space Shuttle program. It is intended to satisfy virtually all of the flight software requirements of the space shuttle. To achieve this, it incorporates a wide range of features, including applications-oriented data types and organizations, real time control mechanisms, and constructs for systems programming tasks. It is a higher order language designed to allow programmers, analysts, and engineers to communicate with the computer in a form approximating natural mathematical expression. Parts of the English language are combined with standard notation to provide a tool that readily encourages programming without demanding computer hardware expertise. Block diagrams and flow charts are included. The semantics of the language is discussed.

  2. Neural Indices of Semantic Processing in Early Childhood Distinguish Eventual Stuttering Persistence and Recovery

    Science.gov (United States)

    Kreidler, Kathryn; Wray, Amanda Hampton; Usler, Evan; Weber, Christine

    2017-01-01

    Purpose: Maturation of neural processes for language may lag in some children who stutter (CWS), and event-related potentials (ERPs) distinguish CWS who have recovered from those who have persisted. The current study explores whether ERPs indexing semantic processing may distinguish children who will eventually persist in stuttering…

  3. Temporal reliability and lateralization of the resting-state language network.

    Science.gov (United States)

    Zhu, Linlin; Fan, Yang; Zou, Qihong; Wang, Jue; Gao, Jia-Hong; Niu, Zhendong

    2014-01-01

    The neural processing loop of language is complex but highly associated with Broca's and Wernicke's areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca's and Wernicke's areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca's area was found to be left lateralized, while the Wernicke's area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR) on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability.

  4. Temporal reliability and lateralization of the resting-state language network.

    Directory of Open Access Journals (Sweden)

    Linlin Zhu

    Full Text Available The neural processing loop of language is complex but highly associated with Broca's and Wernicke's areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca's and Wernicke's areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca's area was found to be left lateralized, while the Wernicke's area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability.

  5. Temporal Reliability and Lateralization of the Resting-State Language Network

    Science.gov (United States)

    Zou, Qihong; Wang, Jue; Gao, Jia-Hong; Niu, Zhendong

    2014-01-01

    The neural processing loop of language is complex but highly associated with Broca's and Wernicke's areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca's and Wernicke's areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca's area was found to be left lateralized, while the Wernicke's area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR) on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability. PMID:24475058

  6. QCD-Aware Neural Networks for Jet Physics

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Recent progress in applying machine learning for jet physics has been built upon an analogy between calorimeters and images. In this work, we present a novel class of recursive neural networks built instead upon an analogy between QCD and natural languages. In the analogy, four-momenta are like words and the clustering history of sequential recombination jet algorithms is like the parsing of a sentence. Our approach works directly with the four-momenta of a variable-length set of particles, and the jet-based neural network topology varies on an event-by-event basis. Our experiments highlight the flexibility of our method for building task-specific jet embeddings and show that recursive architectures are significantly more accurate and data efficient than previous image-based networks. We extend the analogy from individual jets (sentences) to full events (paragraphs), and show for the first time an event-level classifier operating...

  7. Neural System Prediction and Identification Challenge

    Directory of Open Access Journals (Sweden)

    Ioannis eVlachos

    2013-12-01

    Full Text Available Can we infer the function of a biological neural network (BNN if we know the connectivity and activity of all its constituent neurons? This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC. We provide the connectivity and activity of all neurons and invite participants (i to infer the functions implemented (hard-wired in spiking neural networks (SNNs by stimulating and recording the activity of neurons and, (ii to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  8. Neural system prediction and identification challenge.

    Science.gov (United States)

    Vlachos, Ioannis; Zaytsev, Yury V; Spreizer, Sebastian; Aertsen, Ad; Kumar, Arvind

    2013-01-01

    Can we infer the function of a biological neural network (BNN) if we know the connectivity and activity of all its constituent neurons?This question is at the core of neuroscience and, accordingly, various methods have been developed to record the activity and connectivity of as many neurons as possible. Surprisingly, there is no theoretical or computational demonstration that neuronal activity and connectivity are indeed sufficient to infer the function of a BNN. Therefore, we pose the Neural Systems Identification and Prediction Challenge (nuSPIC). We provide the connectivity and activity of all neurons and invite participants (1) to infer the functions implemented (hard-wired) in spiking neural networks (SNNs) by stimulating and recording the activity of neurons and, (2) to implement predefined mathematical/biological functions using SNNs. The nuSPICs can be accessed via a web-interface to the NEST simulator and the user is not required to know any specific programming language. Furthermore, the nuSPICs can be used as a teaching tool. Finally, nuSPICs use the crowd-sourcing model to address scientific issues. With this computational approach we aim to identify which functions can be inferred by systematic recordings of neuronal activity and connectivity. In addition, nuSPICs will help the design and application of new experimental paradigms based on the structure of the SNN and the presumed function which is to be discovered.

  9. The Common Language Question Before International Organizations

    Science.gov (United States)

    Lapenna, Ivo

    1971-01-01

    Third report on a petition submitted to the United Nations by the Universal Esperanto Association (UEA) in 1950 to promote Esperanto as the universal language. The petition was forwarded for action to Unesco which in 1954 resolved to support any efforts in this direction undertaken within a member state. Available from Humanities Press, Inc.,…

  10. Usage of self-organizing neural networks in evaluation of consumer behaviour

    Directory of Open Access Journals (Sweden)

    Jana Weinlichová

    2010-01-01

    Full Text Available This article deals with evaluation of consumer data by Artificial Intelligence methods. In methodical part there are described learning algorithms for Kohonen maps on the principle of supervised learning, unsupervised learning and semi-supervised learning. The principles of supervised learning and unsupervised learning are compared. On base of binding conditions of these principles there is pointed out an advantage of semi-supervised learning. Three algorithms are described for the semi-supervised learning: label propagation, self-training and co-training. Especially usage of co-training in Kohonen map learning seems to be promising point of other research. In concrete application of Kohonen neural network on consumer’s expense the unsupervised learning method has been chosen – the self-organization. So the features of data are evaluated by clustering method called Kohonen maps. These input data represents consumer expenses of households in countries of European union and are characterised by 12-dimension vector according to commodity classification. The data are evaluated in several years, so we can see their distribution, similarity or dissimilarity and also their evolution. In the article we discus other usage of this method for this type of data and also comparison of our results with results reached by hierarchical cluster analysis.

  11. Cognitive Neuroscience of Foreign Language Education: Myths and Realities

    Directory of Open Access Journals (Sweden)

    Ali Nouri

    2015-04-01

    Full Text Available This paper summarizes the educational implications of current research on cognitive neuroscience for foreign-language learning to provide an overview of myths and realities in this appealing area of research. Although the potential benefits of neuroscientific research into language acquisition are great, there are a number of popular myths that none of which are supported by scientific evidence. In this paper, three prominent examples of these myths are introduced and discussed how they are based on misinterpretation and misapplication from neuroscience research. The first pervasive example of such misconception is the prevalent belief of being the certain critical periods for learning a second language. It implies that the opportunity to acquire foreign languages is lost forever by missing these biological windows. In fact, however, extensive research shows that there are sensitive periods, but not critical periods, during which an individual can acquire certain aspects of language with greater ease than at other times. Another example of myths is a false conclusion implies that exposing children to a foreign language too early interrupts knowledge of their first language. The reality is that learning a second language not only improves language abilities in the first language, but also positively affects reading abilities and general literacy in school. Like the other myths, there is also a popular conception about ability to learn second language during sleep. It is demonstrated that previously acquired memories are consolidated and new association are learned during sleep, but learning a foreign language requires conscious effort and available data do not support this hypothesis that second language acquire during sleep. The main conclusion arising from this argument is that, while our understanding of the neural bases of language learning is continually evolving, our interpretation of the implications of these findings for foreign language

  12. Family veto in organ donation in Canada: framing within English-language newspaper articles.

    Science.gov (United States)

    Anthony, Samantha J; Toews, Maeghan; Caulfield, Timothy; Wright, Linda

    2017-10-17

    Because organ transplantation relies on public support for donation, an analysis of public discourse around organ donation is essential. We investigated the portrayal of family veto - when a family overrides the deceased person's prior legally executed wishes to donate - in Canadian news media. Using the Canadian Newsstream database, we identified articles published in English-language newspapers addressing family veto between 2000 and 2016. Guided by the theoretical perspectives of framing of media effects, we conducted a systematic content analysis of the articles to examine how the Canadian media framed family veto. An initial in-depth analysis of the data set in which themes and patterns were captured and recorded identified coding categories, including primary framing of family veto, prevalence, reasons, ethical or legal concerns and overall tone of the article. Two coders analyzed the data set to ensure intercoder reliability. A total of 133 relevant articles were identified. Family veto was framed predominantly as something that should not be allowed (81 articles [60.9%]) and as a reality that is little understood outside the transplantation community (45 [33.8%]). One-quarter of the articles (32 [24.1%]) highlighted ethical principles of autonomy and justice associated with family veto. Family veto was represented as a stumbling block in the present organ donation system, with most publications (107 [80.4%]) calling for change. There were differing interpretations of organ donation legislation, with 82 articles (61.6%) erroneously stating or suggesting that existing legislation permits family veto. Family veto in organ donation was portrayed predominantly negatively. Many publications reflected a misunderstanding of the law concerning this issue. Although the framing of family veto highlighted important ethical and legal concerns as well as practice and policy considerations, research is needed to enhance the understanding of family veto in organ donation

  13. Brain signal variability as a window into the bidirectionality between music and language processing: moving from a linear to a nonlinear model.

    Science.gov (United States)

    Hutka, Stefanie; Bidelman, Gavin M; Moreno, Sylvain

    2013-12-30

    There is convincing empirical evidence for bidirectional transfer between music and language, such that experience in either domain can improve mental processes required by the other. This music-language relationship has been studied using linear models (e.g., comparing mean neural activity) that conceptualize brain activity as a static entity. The linear approach limits how we can understand the brain's processing of music and language because the brain is a nonlinear system. Furthermore, there is evidence that the networks supporting music and language processing interact in a nonlinear manner. We therefore posit that the neural processing and transfer between the domains of language and music are best viewed through the lens of a nonlinear framework. Nonlinear analysis of neurophysiological activity may yield new insight into the commonalities, differences, and bidirectionality between these two cognitive domains not measurable in the local output of a cortical patch. We thus propose a novel application of brain signal variability (BSV) analysis, based on mutual information and signal entropy, to better understand the bidirectionality of music-to-language transfer in the context of a nonlinear framework. This approach will extend current methods by offering a nuanced, network-level understanding of the brain complexity involved in music-language transfer.

  14. Brain signal variability as a window into the bidirectionality between music and language processing: Moving from a linear to a nonlinear model

    Directory of Open Access Journals (Sweden)

    Stefanie Andrea Hutka

    2013-12-01

    Full Text Available There is convincing empirical evidence for bidirectional transfer between music and language, such that experience in either domain can improve mental processes required by the other. This music-language relationship has been studied using linear models (e.g., comparing mean neural activity that conceptualize brain activity as a static entity. The linear approach limits how we can understand the brain’s processing of music and language because the brain is a nonlinear system. Furthermore, there is evidence that the networks supporting music and language processing interact in a nonlinear manner. We therefore posit that the neural processing and transfer between the domains of language and music are best viewed through the lens of a nonlinear framework. Nonlinear analysis of neurophysiological activity may yield new insight into the commonalities, differences, and bidirectionality between these two cognitive domains not measurable in the local output of a cortical patch. We thus propose a novel application of brain signal variability (BSV analysis, based on mutual information and signal entropy, to better understand the bidirectionality of music-to-language transfer in the context of a nonlinear framework. This approach will extend current methods by offering a nuanced, network-level understanding of the brain complexity involved in music-language transfer.

  15. Longitudinal changes in resting-state fMRI from age 5 to age 6years covary with language development.

    Science.gov (United States)

    Xiao, Yaqiong; Friederici, Angela D; Margulies, Daniel S; Brauer, Jens

    2016-03-01

    Resting-state functional magnetic resonance imaging is a powerful technique to study the whole-brain neural connectivity that underlies cognitive systems. The present study aimed to define the changes in neural connectivity in their relation to language development. Longitudinal resting-state functional data were acquired from a cohort of preschool children at age 5 and one year later, and changes in functional connectivity were correlated with language performance in sentence comprehension. For this, degree centrality, a voxel-based network measure, was used to assess age-related differences in connectivity at the whole-brain level. Increases in connectivity with age were found selectively in a cluster within the left posterior superior temporal gyrus and sulcus (STG/STS). In order to further specify the connection changes, a secondary seed-based functional connectivity analysis on this very cluster was performed. The correlations between resting-state functional connectivity (RSFC) and language performance revealed developmental effects with age and, importantly, also dependent on the advancement in sentence comprehension ability over time. In children with greater advancement in language abilities, the behavioral improvement was positively correlated with RSFC increase between left posterior STG/STS and other regions of the language network, i.e., left and right inferior frontal cortex. The age-related changes observed in this study provide evidence for alterations in the language network as language develops and demonstrates the viability of this approach for the investigation of normal and aberrant language development. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  16. TexMo: A Multi-language Development Environment

    DEFF Research Database (Denmark)

    Pfeiffer, Rolf-Helge; Wasowski, Andrzej

    2012-01-01

    Contemporary software systems contain a large number of artifacts expressed in multiple languages, ranging from domain-specific languages to general purpose languages. These artifacts are interrelated to form software systems. Existing development environments insufficiently support handling...... relations between artifacts in multiple languages. This paper presents a taxonomy for multi-language development environments, organized according to language representation, representation of relations between languages, and types of these relations. Additionally, we present TexMo, a prototype of a multi-language...... development environment, which uses an explicit relation model and implements visualization, static checking, navigation, and refactoring of cross-language relations. We evaluate TexMo by applying it to development of a web-application, JTrac, and provide preliminary evidence of its feasibility by running...

  17. Empirical tests of a theory of language, mathematics, and matter.

    Science.gov (United States)

    Abler, William L

    2008-01-01

    In an earlier paper (Abler, 2006), I proposed a theory of language, especially sentences, based on the symmetrical structure of the equation. Here, I use the structure of equations to deduce neural structures (e.g., mirror neurons or intra-cellular macromolecules, or crystals, or resonations) that might generate them. Ultimately, the properties described are a consequence of dimensional properties of matter

  18. Brain responses in 4-month-old infants are already language specific.

    Science.gov (United States)

    Friederici, Angela D; Friedrich, Manuela; Christophe, Anne

    2007-07-17

    Language is the most important faculty that distinguishes humans from other animals. Infants learn their native language fast and effortlessly during the first years of life, as a function of the linguistic input in their environment. Behavioral studies reported the discrimination of melodic contours [1] and stress patterns [2, 3] in 1-4-month-olds. Behavioral [4, 5] and brain measures [6-8] have shown language-independent discrimination of phonetic contrasts at that age. Language-specific discrimination, however, has been reported for phonetic contrasts only for 6-12-month-olds [9-12]. Here we demonstrate language-specific discrimination of stress patterns in 4-month-old German and French infants by using electrophysiological brain measures. We compare the processing of disyllabic words differing in their rhythmic structure, mimicking German words being stressed on the first syllable, e.g., pápa/daddy[13], and French ones being stressed on the second syllable, e.g., papá/daddy. Event-related brain potentials reveal that experience with German and French differentially affects the brain responses of 4-month-old infants, with each language group displaying a processing advantage for the rhythmic structure typical in its native language. These data indicate language-specific neural representations of word forms in the infant brain as early as 4 months of age.

  19. 23rd Workshop of the Italian Neural Networks Society (SIREN)

    CERN Document Server

    Esposito, Anna; Morabito, Francesco

    2014-01-01

    This volume collects a selection of contributions which has been presented at the 23rd Italian Workshop on Neural Networks, the yearly meeting of the Italian Society for Neural Networks (SIREN). The conference was held in Vietri sul Mare, Salerno, Italy during May 23-24, 2013. The annual meeting of SIREN is sponsored by International Neural Network Society (INNS), European Neural Network Society (ENNS) and IEEE Computational Intelligence Society (CIS). The book – as well as the workshop-  is organized in two main components, a special session and a group of regular sessions featuring different aspects and point of views of artificial neural networks, artificial and natural intelligence, as well as psychological and cognitive theories for modeling human behaviors and human machine interactions, including Information Communication applications of compelling interest.  .

  20. Thought and Language in Cognitive Science

    Directory of Open Access Journals (Sweden)

    Destéfano, Mariela

    2012-01-01

    Full Text Available In cognitive science, the discussion about the relations between language and thought is very heterogeneous. It involves developments on linguistics, philosophy, psychology, etc. Carruthers and Boucher (1998 identify different criteria that would organize the diversity of positions about language and thought assumed in linguistics, philosophy and psychology. One of them is the constitution thesis (CT, which establishes that language is constitutively involved in thought. In this paper I would like to show some problems of CT in order to understand the relation between language and thought in cognitive science.

  1. Testing the Language of German Cerebral Palsy Patients with Right Hemispheric Language Organization after Early Left Hemispheric Damage

    Science.gov (United States)

    Schwilling, Eleonore; Krageloh-Mann, Ingeborg; Konietzko, Andreas; Winkler, Susanne; Lidzba, Karen

    2012-01-01

    Language functions are generally represented in the left cerebral hemisphere. After early (prenatally acquired or perinatally acquired) left hemispheric brain damage language functions may be salvaged by reorganization into the right hemisphere. This is different from brain lesions acquired in adulthood which normally lead to aphasia. Right…

  2. A Neural Marker for Social Bias Toward In-group Accents.

    Science.gov (United States)

    Bestelmeyer, Patricia E G; Belin, Pascal; Ladd, D Robert

    2015-10-01

    Accents provide information about the speaker's geographical, socio-economic, and ethnic background. Research in applied psychology and sociolinguistics suggests that we generally prefer our own accent to other varieties of our native language and attribute more positive traits to it. Despite the widespread influence of accents on social interactions, educational and work settings the neural underpinnings of this social bias toward our own accent and, what may drive this bias, are unexplored. We measured brain activity while participants from two different geographical backgrounds listened passively to 3 English accent types embedded in an adaptation design. Cerebral activity in several regions, including bilateral amygdalae, revealed a significant interaction between the participants' own accent and the accent they listened to: while repetition of own accents elicited an enhanced neural response, repetition of the other group's accent resulted in reduced responses classically associated with adaptation. Our findings suggest that increased social relevance of, or greater emotional sensitivity to in-group accents, may underlie the own-accent bias. Our results provide a neural marker for the bias associated with accents, and show, for the first time, that the neural response to speech is partly shaped by the geographical background of the listener. © The Author 2014. Published by Oxford University Press.

  3. Changes in White-Matter Connectivity in Late Second Language Learners: Evidence from Diffusion Tensor Imaging

    Directory of Open Access Journals (Sweden)

    Eleonora Rossi

    2017-11-01

    Full Text Available Morphological brain changes as a consequence of new learning have been widely established. Learning a second language (L2 is one such experience that can lead to rapid structural neural changes. However, still relatively little is known about how levels of proficiency in the L2 and the age at which the L2 is learned influence brain neuroplasticity. The goal of this study is to provide novel evidence for the effect of bilingualism on white matter structure in relatively proficient but late L2 learners who acquired the second language after early childhood. Overall, the results demonstrate a significant effect on white matter fractional anisotropy (FA as a function of L2 learning. Higher FA values were found in a broad white matter network including the anterior thalamic radiation (ATR, the inferior fronto-occipital fasciculus (IFOF, the Uncinate Fasciculus (UF, and the inferior longitudinal fasciculus (ILF. Moreover, FA values were correlated with age of L2 acquisition, suggesting that learning an L2, even past childhood, induces neural changes. Finally, these results provide some initial evidence that variability in the age of L2 acquisition has important consequences for neural plasticity.

  4. Comparing and validating methods of reading instruction using behavioural and neural findings in an artificial orthography.

    Science.gov (United States)

    Taylor, J S H; Davis, Matthew H; Rastle, Kathleen

    2017-06-01

    There is strong scientific consensus that emphasizing print-to-sound relationships is critical when learning to read alphabetic languages. Nevertheless, reading instruction varies across English-speaking countries, from intensive phonic training to multicuing environments that teach sound- and meaning-based strategies. We sought to understand the behavioral and neural consequences of these differences in relative emphasis. We taught 24 English-speaking adults to read 2 sets of 24 novel words (e.g., /buv/, /sig/), written in 2 different unfamiliar orthographies. Following pretraining on oral vocabulary, participants learned to read the novel words over 8 days. Training in 1 language was biased toward print-to-sound mappings while training in the other language was biased toward print-to-meaning mappings. Results showed striking benefits of print-sound training on reading aloud, generalization, and comprehension of single words. Univariate analyses of fMRI data collected at the end of training showed that print-meaning relative to print-sound relative training increased neural effort in dorsal pathway regions involved in reading aloud. Conversely, activity in ventral pathway brain regions involved in reading comprehension was no different following print-meaning versus print-sound training. Multivariate analyses validated our artificial language approach, showing high similarity between the spatial distribution of fMRI activity during artificial and English word reading. Our results suggest that early literacy education should focus on the systematicities present in print-to-sound relationships in alphabetic languages, rather than teaching meaning-based strategies, in order to enhance both reading aloud and comprehension of written words. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  5. Processing abstract language modulates motor system activity.

    Science.gov (United States)

    Glenberg, Arthur M; Sato, Marc; Cattaneo, Luigi; Riggio, Lucia; Palumbo, Daniele; Buccino, Giovanni

    2008-06-01

    Embodiment theory proposes that neural systems for perception and action are also engaged during language comprehension. Previous neuroimaging and neurophysiological studies have only been able to demonstrate modulation of action systems during comprehension of concrete language. We provide neurophysiological evidence for modulation of motor system activity during the comprehension of both concrete and abstract language. In Experiment 1, when the described direction of object transfer or information transfer (e.g., away from the reader to another) matched the literal direction of a hand movement used to make a response, speed of responding was faster than when the two directions mismatched (an action-sentence compatibility effect). In Experiment 2, we used single-pulse transcranial magnetic stimulation to study changes in the corticospinal motor pathways to hand muscles while reading the same sentences. Relative to sentences that do not describe transfer, there is greater modulation of activity in the hand muscles when reading sentences describing transfer of both concrete objects and abstract information. These findings are discussed in relation to the human mirror neuron system.

  6. Distributed Language and Dialogism

    DEFF Research Database (Denmark)

    Steffensen, Sune Vork

    2015-01-01

    addresses Linell’s critique of Distributed Language as rooted in biosemiotics and in theories of organism-environment systems. It is argued that Linell’s sense-based approach entails an individualist view of how conspecific Others acquire their status as prominent parts of the sense-maker’s environment......This article takes a starting point in Per Linell’s (2013) review article on the book Distributed Language (Cowley, 2011a) and other contributions to the field of ‘Distributed Language’, including Cowley et al. (2010) and Hodges et al. (2012). The Distributed Language approach is a naturalistic...... and anti-representational approach to language that builds on recent developments in the cognitive sciences. With a starting point in Linell’s discussion of the approach, the article aims to clarify four aspects of a distributed view of language vis-à-vis the tradition of Dialogism, as presented by Linell...

  7. STUDY OF SOLUTION REPRESENTATION LANGUAGE INFLUENCE ON EFFICIENCY OF INTEGER SEQUENCES PREDICTION

    Directory of Open Access Journals (Sweden)

    A. S. Potapov

    2015-01-01

    Full Text Available Methods based on genetic programming for the problem solution of integer sequences extrapolation are the subjects for study in the paper. In order to check the hypothesis about the influence of language expression of program representation on the prediction effectiveness, the genetic programming method based on several limited languages for recurrent sequences has been developed. On the single sequence sample the implemented method with the use of more complete language has shown results, significantly better than the results of one of the current methods represented in literature based on artificial neural networks. Analysis of experimental comparison results for the realized method with the usage of different languages has shown that language extension increases the difficulty of consistent patterns search in languages, available for prediction in a simpler language though it makes new sequence classes accessible for prediction. This effect can be reduced but not eliminated completely at language extension by the constructions, which make solutions more compact. Carried out researches have drawn to the conclusion that alone the choice of an adequate language for solution representation is not enough for the full problem solution of integer sequences prediction (and, all the more, universal prediction problem. However, practically applied methods can be received by the usage of genetic programming.

  8. Prospective Foreign Language Teachers' Preference of Teaching Methods for the Language Acquisition Course in Turkish Higher Education

    Science.gov (United States)

    GüvendIr, Emre

    2013-01-01

    Considering the significance of taking student preferences into account while organizing teaching practices, the current study explores which teaching method prospective foreign language teachers mostly prefer their teacher to use in the language acquisition course. A teaching methods evaluation form that includes six commonly used teaching…

  9. Use of Artificial Neural Network Models to Predict Indicator Organism Concentrations in an Urban Watershed

    Science.gov (United States)

    Mas, D. M.; Ahlfeld, D. P.

    2004-05-01

    Forecasting stream water quality is important for numerous aspects of resource protection and management. Fecal coliform and enteroccocus are primary indicator organisms used to assess potential pathogen contamination. Consequently, modeling the occurrence and concentration of fecal coliform and enterococcus is an important tool in watershed management. In addition, analyzing the relationship between model input and predicted indicator organisms is useful for elucidating possible sources of contamination and mechanisms of transport. While many process-based, statistical, and empirical models exist for water quality prediction, artificial neural network (ANN) models are increasingly being used for forecasting of water resources variables because ANNs are often capable of modeling complex systems for which behavioral rules are either unknown or difficult to simulate. The performance of ANNs compared to more established modeling approaches such as multiple linear regression (MLR) remains an importance research question. Data collected the U.S. Geological Survey in the lower Charles River in Massachusetts, USA in 1999-2000 was examined to determine correlation between various water quality constituents and indicator organisms and to explore the relationship between rainfall characteristics and indicator organism concentrations. Using the results of the statistical analysis to guide the selection of explanatory variables, MLR was performed to develop predictive equations for wet weather and dry weather conditions. The results show that the best-performing predictor variables are generally consistent for both indicator organisms considered. In addition, the regression equations show increasing indicator organism concentrations as a function of suspended sediment concentrations and length of time since last precipitation event, suggesting accumulation and wash off as a key mechanism of pathogen transport under wet weather conditions. This research also presents the

  10. Universal brain signature of proficient reading: Evidence from four contrasting languages.

    Science.gov (United States)

    Rueckl, Jay G; Paz-Alonso, Pedro M; Molfese, Peter J; Kuo, Wen-Jui; Bick, Atira; Frost, Stephen J; Hancock, Roeland; Wu, Denise H; Mencl, William Einar; Duñabeitia, Jon Andoni; Lee, Jun-Ren; Oliver, Myriam; Zevin, Jason D; Hoeft, Fumiko; Carreiras, Manuel; Tzeng, Ovid J L; Pugh, Kenneth R; Frost, Ram

    2015-12-15

    We propose and test a theoretical perspective in which a universal hallmark of successful literacy acquisition is the convergence of the speech and orthographic processing systems onto a common network of neural structures, regardless of how spoken words are represented orthographically in a writing system. During functional MRI, skilled adult readers of four distinct and highly contrasting languages, Spanish, English, Hebrew, and Chinese, performed an identical semantic categorization task to spoken and written words. Results from three complementary analytic approaches demonstrate limited language variation, with speech-print convergence emerging as a common brain signature of reading proficiency across the wide spectrum of selected languages, whether their writing system is alphabetic or logographic, whether it is opaque or transparent, and regardless of the phonological and morphological structure it represents.

  11. The Processing of Biologically Plausible and Implausible forms in American Sign Language: Evidence for Perceptual Tuning.

    Science.gov (United States)

    Almeida, Diogo; Poeppel, David; Corina, David

    The human auditory system distinguishes speech-like information from general auditory signals in a remarkably fast and efficient way. Combining psychophysics and neurophysiology (MEG), we demonstrate a similar result for the processing of visual information used for language communication in users of sign languages. We demonstrate that the earliest visual cortical responses in deaf signers viewing American Sign Language (ASL) signs show specific modulations to violations of anatomic constraints that would make the sign either possible or impossible to articulate. These neural data are accompanied with a significantly increased perceptual sensitivity to the anatomical incongruity. The differential effects in the early visual evoked potentials arguably reflect an expectation-driven assessment of somatic representational integrity, suggesting that language experience and/or auditory deprivation may shape the neuronal mechanisms underlying the analysis of complex human form. The data demonstrate that the perceptual tuning that underlies the discrimination of language and non-language information is not limited to spoken languages but extends to languages expressed in the visual modality.

  12. A Common Neural Substrate for Language Production and Verbal Working Memory

    Science.gov (United States)

    Acheson, Daniel J.; Hamidi, Massihullah; Binder, Jeffrey R.; Postle, Bradley R.

    2011-01-01

    Verbal working memory (VWM), the ability to maintain and manipulate representations of speech sounds over short periods, is held by some influential models to be independent from the systems responsible for language production and comprehension [e.g., Baddeley, A. D. "Working memory, thought, and action." New York, NY: Oxford University Press,…

  13. Lexical-Semantic Organization in Bilingually Developing Deaf Children with ASL-Dominant Language Exposure: Evidence from a Repeated Meaning Association Task

    Science.gov (United States)

    Mann, Wolfgang; Sheng, Li; Morgan, Gary

    2016-01-01

    This study compared the lexical-semantic organization skills of bilingually developing deaf children in American Sign Language (ASL) and English with those of a monolingual hearing group. A repeated meaning-association paradigm was used to assess retrieval of semantic relations in deaf 6-10-year-olds exposed to ASL from birth by their deaf…

  14. A Study of Recurrent and Convolutional Neural Networks in the Native Language Identification Task

    KAUST Repository

    Werfelmann, Robert

    2018-01-01

    around the world. The neural network models consisted of Long Short-Term Memory and Convolutional networks using the sentences of each document as the input. Additional statistical features were generated from the text to complement the predictions

  15. The neural basis for writing from dictation in the temporoparietal cortex.

    Science.gov (United States)

    Roux, Franck-Emmanuel; Durand, Jean-Baptiste; Réhault, Emilie; Planton, Samuel; Draper, Louisa; Démonet, Jean-François

    2014-01-01

    Cortical electrical stimulation mapping was used to study neural substrates of the function of writing in the temporoparietal cortex. We identified the sites involved in oral language (sentence reading and naming) and writing from dictation, in order to spare these areas during removal of brain tumours in 30 patients (23 in the left, and 7 in the right hemisphere). Electrostimulation of the cortex impaired writing ability in 62 restricted cortical areas (.25 cm2). These were found in left temporoparietal lobes and were mostly located along the superior temporal gyrus (Brodmann's areas 22 and 42). Stimulation of right temporoparietal lobes in right-handed patients produced no writing impairments. However there was a high variability of location between individuals. Stimulation resulted in combined symptoms (affecting oral language and writing) in fourteen patients, whereas in eight other patients, stimulation-induced pure agraphia symptoms with no oral language disturbance in twelve of the identified areas. Each detected area affected writing in a different way. We detected the various different stages of the auditory-to-motor pathway of writing from dictation: either through comprehension of the dictated sentences (word deafness areas), lexico-semantic retrieval, or phonologic processing. In group analysis, barycentres of all different types of writing interferences reveal a hierarchical functional organization along the superior temporal gyrus from initial word recognition to lexico-semantic and phonologic processes along the ventral and the dorsal comprehension pathways, supporting the previously described auditory-to-motor process. The left posterior Sylvian region supports different aspects of writing function that are extremely specialized and localized, sometimes being segregated in a way that could account for the occurrence of pure agraphia that has long-been described in cases of damage to this region. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Neural Substrates of Interactive Musical Improvisation: An fMRI Study of ‘Trading Fours’ in Jazz

    Science.gov (United States)

    Donnay, Gabriel F.; Rankin, Summer K.; Lopez-Gonzalez, Monica; Jiradejvong, Patpong; Limb, Charles J.

    2014-01-01

    Interactive generative musical performance provides a suitable model for communication because, like natural linguistic discourse, it involves an exchange of ideas that is unpredictable, collaborative, and emergent. Here we show that interactive improvisation between two musicians is characterized by activation of perisylvian language areas linked to processing of syntactic elements in music, including inferior frontal gyrus and posterior superior temporal gyrus, and deactivation of angular gyrus and supramarginal gyrus, brain structures directly implicated in semantic processing of language. These findings support the hypothesis that musical discourse engages language areas of the brain specialized for processing of syntax but in a manner that is not contingent upon semantic processing. Therefore, we argue that neural regions for syntactic processing are not domain-specific for language but instead may be domain-general for communication. PMID:24586366

  17. Clinical Assistant Diagnosis for Electronic Medical Record Based on Convolutional Neural Network.

    Science.gov (United States)

    Yang, Zhongliang; Huang, Yongfeng; Jiang, Yiran; Sun, Yuxi; Zhang, Yu-Jin; Luo, Pengcheng

    2018-04-20

    Automatically extracting useful information from electronic medical records along with conducting disease diagnoses is a promising task for both clinical decision support(CDS) and neural language processing(NLP). Most of the existing systems are based on artificially constructed knowledge bases, and then auxiliary diagnosis is done by rule matching. In this study, we present a clinical intelligent decision approach based on Convolutional Neural Networks(CNN), which can automatically extract high-level semantic information of electronic medical records and then perform automatic diagnosis without artificial construction of rules or knowledge bases. We use collected 18,590 copies of the real-world clinical electronic medical records to train and test the proposed model. Experimental results show that the proposed model can achieve 98.67% accuracy and 96.02% recall, which strongly supports that using convolutional neural network to automatically learn high-level semantic features of electronic medical records and then conduct assist diagnosis is feasible and effective.

  18. Inhibitory non-invasive brain stimulation to homologous language regions as an adjunct to speech and language therapy in post-stroke aphasia: a meta-analysis

    Directory of Open Access Journals (Sweden)

    Begonya eOtal

    2015-04-01

    Full Text Available Chronic communication impairment is common after stroke, and conventional speech and language therapy (SLT strategies have limited effectiveness in post-stroke aphasia. Neurorehabilitation with non-invasive brain stimulation techniques (NIBS ‒ particularly repetitive transcranial magnetic stimulation (rTMS or transcranial direct current stimulation (tDCS ‒ may enhance the effects of SLT in selected patients. Applying inhibitory NIBS to specific homologous language regions may induce neural reorganization and reduce interhemispheric competition. This mini review highlights randomized controlled trials (RCTs and randomized cross-over trials using low-frequency rTMS or cathodal tDCS over the non-lesioned non-language dominant hemisphere and performs an exploratory meta-analysis of those trials considered combinable. Using a random-effects model, a meta-analysis of nine eligible trials involving 215 participants showed a significant mean effect size of 0.51 (95% CI = 0.24 to 0.79 for the main outcome accuracy of naming in language assessment. No heterogeneity was observed (I2 = 0%. More multicenter RCTs with larger populations and homogenous intervention protocols are required to confirm these and the longer-term effects.

  19. Structured Memory for Neural Turing Machines

    OpenAIRE

    Zhang, Wei; Yu, Yang; Zhou, Bowen

    2015-01-01

    Neural Turing Machines (NTM) contain memory component that simulates "working memory" in the brain to store and retrieve information to ease simple algorithms learning. So far, only linearly organized memory is proposed, and during experiments, we observed that the model does not always converge, and overfits easily when handling certain tasks. We think memory component is key to some faulty behaviors of NTM, and better organization of memory component could help fight those problems. In this...

  20. Generating Seismograms with Deep Neural Networks

    Science.gov (United States)

    Krischer, L.; Fichtner, A.

    2017-12-01

    The recent surge of successful uses of deep neural networks in computer vision, speech recognition, and natural language processing, mainly enabled by the availability of fast GPUs and extremely large data sets, is starting to see many applications across all natural sciences. In seismology these are largely confined to classification and discrimination tasks. In this contribution we explore the use of deep neural networks for another class of problems: so called generative models.Generative modelling is a branch of statistics concerned with generating new observed data samples, usually by drawing from some underlying probability distribution. Samples with specific attributes can be generated by conditioning on input variables. In this work we condition on seismic source (mechanism and location) and receiver (location) parameters to generate multi-component seismograms.The deep neural networks are trained on synthetic data calculated with Instaseis (http://instaseis.net, van Driel et al. (2015)) and waveforms from the global ShakeMovie project (http://global.shakemovie.princeton.edu, Tromp et al. (2010)). The underlying radially symmetric or smoothly three dimensional Earth structures result in comparatively small waveform differences from similar events or at close receivers and the networks learn to interpolate between training data samples.Of particular importance is the chosen misfit functional. Generative adversarial networks (Goodfellow et al. (2014)) implement a system in which two networks compete: the generator network creates samples and the discriminator network distinguishes these from the true training examples. Both are trained in an adversarial fashion until the discriminator can no longer distinguish between generated and real samples. We show how this can be applied to seismograms and in particular how it compares to networks trained with more conventional misfit metrics. Last but not least we attempt to shed some light on the black-box nature of

  1. Documentary languages and knowledge organization systems in the context of the semantic web

    Directory of Open Access Journals (Sweden)

    Marilda Lopes Ginez de Lara

    Full Text Available The aim of this study was to discuss the need for formal documentary languages as a condition for it to function in the Semantic Web. Based on a bibliographic review, Linked Open Data is presented as an initial condition for the operationalization of the Semantic Web, similar to the movement of Linked Open Vocabularies that aimed to promote interoperability among vocabularies. We highlight the Simple Knowledge Organization System format by analyzing its main characteristics and presenting the new standard ISO 25964-1/2:2011/2012 -Thesauri and interoperability with other vocabularies, that revises previous recommendations, adding requirements for the interoperability and mapping of vocabularies. We discuss conceptual problems in the formalization of vocabularies and the need to invest critically in its operationalization, suggesting alternatives to harness the mapping of vocabularies.

  2. Sign Language Planning in the Netherlands between 1980 and 2010

    Science.gov (United States)

    Schermer, Trude

    2012-01-01

    This article discusses several aspects of language planning with respect to Sign Language of the Netherlands, or Nederlandse Gebarentaal (NGT). For nearly thirty years members of the Deaf community, the Dutch Deaf Council (Dovenschap) have been working together with researchers, several organizations in deaf education, and the organization of…

  3. Toward a Neural Chronometry for the Aesthetic Experience of Music

    OpenAIRE

    Brattico, Elvira; Bogert, Brigitte; Jacobsen, Thomas

    2013-01-01

    Music is often studied as a cognitive domain alongside language. The emotional aspects of music have also been shown to be important, but views on their nature diverge. For instance, the specific emotions that music induces and how they relate to emotional expression are still under debate. Here we propose a mental and neural chronometry of the aesthetic experience of music initiated and mediated by external and internal contexts such as intentionality, background mood, attention, and experti...

  4. Neural entrainment to rhythmically-presented auditory, visual and audio-visual speech in children

    Directory of Open Access Journals (Sweden)

    Alan James Power

    2012-07-01

    Full Text Available Auditory cortical oscillations have been proposed to play an important role in speech perception. It is suggested that the brain may take temporal ‘samples’ of information from the speech stream at different rates, phase-resetting ongoing oscillations so that they are aligned with similar frequency bands in the input (‘phase locking’. Information from these frequency bands is then bound together for speech perception. To date, there are no explorations of neural phase-locking and entrainment to speech input in children. However, it is clear from studies of language acquisition that infants use both visual speech information and auditory speech information in learning. In order to study neural entrainment to speech in typically-developing children, we use a rhythmic entrainment paradigm (underlying 2 Hz or delta rate based on repetition of the syllable ba, presented in either the auditory modality alone, the visual modality alone, or as auditory-visual speech (via a talking head. To ensure attention to the task, children aged 13 years were asked to press a button as fast as possible when the ba stimulus violated the rhythm for each stream type. Rhythmic violation depended on delaying the occurrence of a ba in the isochronous stream. Neural entrainment was demonstrated for all stream types, and individual differences in standardized measures of language processing were related to auditory entrainment at the theta rate. Further, there was significant modulation of the preferred phase of auditory entrainment in the theta band when visual speech cues were present, indicating cross-modal phase resetting. The rhythmic entrainment paradigm developed here offers a method for exploring individual differences in oscillatory phase locking during development. In particular, a method for assessing neural entrainment and cross-modal phase resetting would be useful for exploring developmental learning difficulties thought to involve temporal sampling

  5. A Functional Magnetic Resonance Imaging Study of Foreign-Language Vocabulary Learning Enhanced by Phonological Rehearsal: The Role of the Right Cerebellum and Left Fusiform Gyrus

    Science.gov (United States)

    Makita, Kai; Yamazaki, Mika; Tanabe, Hiroki C.; Koike, Takahiko; Kochiyama, Takanori; Yokokawa, Hirokazu; Yoshida, Haruyo; Sadato, Norihiro

    2013-01-01

    Psychological research suggests that foreign-language vocabulary acquisition recruits the phonological loop for verbal working memory. To depict the neural underpinnings and shed light on the process of foreign language learning, we conducted functional magnetic resonance imaging of Japanese participants without previous exposure to the Uzbek…

  6. Neural dynamics of morphological processing in spoken word comprehension: Laterality and automaticity

    Directory of Open Access Journals (Sweden)

    Caroline M. Whiting

    2013-11-01

    Full Text Available Rapid and automatic processing of grammatical complexity is argued to take place during speech comprehension, engaging a left-lateralised fronto-temporal language network. Here we address how neural activity in these regions is modulated by the grammatical properties of spoken words. We used combined magneto- and electroencephalography (MEG, EEG to delineate the spatiotemporal patterns of activity that support the recognition of morphologically complex words in English with inflectional (-s and derivational (-er affixes (e.g. bakes, baker. The mismatch negativity (MMN, an index of linguistic memory traces elicited in a passive listening paradigm, was used to examine the neural dynamics elicited by morphologically complex words. Results revealed an initial peak 130-180 ms after the deviation point with a major source in left superior temporal cortex. The localisation of this early activation showed a sensitivity to two grammatical properties of the stimuli: 1 the presence of morphological complexity, with affixed words showing increased left-laterality compared to non-affixed words; and 2 the grammatical category, with affixed verbs showing greater left-lateralisation in inferior frontal gyrus compared to affixed nouns (bakes vs. beaks. This automatic brain response was additionally sensitive to semantic coherence (the meaning of the stem vs. the meaning of the whole form in fronto-temporal regions. These results demonstrate that the spatiotemporal pattern of neural activity in spoken word processing is modulated by the presence of morphological structure, predominantly engaging the left-hemisphere’s fronto-temporal language network, and does not require focused attention on the linguistic input.

  7. Music Training Program: A Method Based on Language Development and Principles of Neuroscience to Optimize Speech and Language Skills in Hearing-Impaired Children

    Directory of Open Access Journals (Sweden)

    Samaneh Sadat Dastgheib

    2013-03-01

    Full Text Available Introduction: In recent years, music has been employed in many intervention and rehabilitation program to enhance cognitive abilities in patients. Numerous researches show that music therapy can help improving language skills in patients including hearing impaired. In this study, a new method of music training is introduced based on principles of neuroscience and capabilities of Persian language to optimize language development in deaf children after implantation.    Materials and Methods: The candidate children are classified in three groups according to their hearing age and language development. The music training program is established and centered on four principles, as follows: hearing and listening to music (with special attention to boost hearing, singing, rhythmic movements with music and playing musical instruments.   Results: Recently much research has demonstrated that even after cochlear implant operation, a child cannot acquire language to the same level of detail as a normal child. As a result of this study music could compensate this developmental delay .It is known that the greater the area of the brain that is activated, the more synaptic learning and plasticity changes occur in that specific area. According to the principles of neural plasticity, music could improve language skills by activating the same areas for language processing in the brain.   Conclusion:  In conclusion, the effects of music on the human brain seem to be very promising and therapeutic in various types of disorders and conditions, including cochlear implantation.

  8. Gestures, vocalizations, and memory in language origins.

    Science.gov (United States)

    Aboitiz, Francisco

    2012-01-01

    THIS ARTICLE DISCUSSES THE POSSIBLE HOMOLOGIES BETWEEN THE HUMAN LANGUAGE NETWORKS AND COMPARABLE AUDITORY PROJECTION SYSTEMS IN THE MACAQUE BRAIN, IN AN ATTEMPT TO RECONCILE TWO EXISTING VIEWS ON LANGUAGE EVOLUTION: one that emphasizes hand control and gestures, and the other that emphasizes auditory-vocal mechanisms. The capacity for language is based on relatively well defined neural substrates whose rudiments have been traced in the non-human primate brain. At its core, this circuit constitutes an auditory-vocal sensorimotor circuit with two main components, a "ventral pathway" connecting anterior auditory regions with anterior ventrolateral prefrontal areas, and a "dorsal pathway" connecting auditory areas with parietal areas and with posterior ventrolateral prefrontal areas via the arcuate fasciculus and the superior longitudinal fasciculus. In humans, the dorsal circuit is especially important for phonological processing and phonological working memory, capacities that are critical for language acquisition and for complex syntax processing. In the macaque, the homolog of the dorsal circuit overlaps with an inferior parietal-premotor network for hand and gesture selection that is under voluntary control, while vocalizations are largely fixed and involuntary. The recruitment of the dorsal component for vocalization behavior in the human lineage, together with a direct cortical control of the subcortical vocalizing system, are proposed to represent a fundamental innovation in human evolution, generating an inflection point that permitted the explosion of vocal language and human communication. In this context, vocal communication and gesturing have a common history in primate communication.

  9. DNA methyltransferase 3b is dispensable for mouse neural crest development.

    Directory of Open Access Journals (Sweden)

    Bridget T Jacques-Fricke

    Full Text Available The neural crest is a population of multipotent cells that migrates extensively throughout vertebrate embryos to form diverse structures. Mice mutant for the de novo DNA methyltransferase DNMT3b exhibit defects in two neural crest derivatives, the craniofacial skeleton and cardiac ventricular septum, suggesting that DNMT3b activity is necessary for neural crest development. Nevertheless, the requirement for DNMT3b specifically in neural crest cells, as opposed to interacting cell types, has not been determined. Using a conditional DNMT3b allele crossed to the neural crest cre drivers Wnt1-cre and Sox10-cre, neural crest DNMT3b mutants were generated. In both neural crest-specific and fully DNMT3b-mutant embryos, cranial neural crest cells exhibited only subtle migration defects, with increased numbers of dispersed cells trailing organized streams in the head. In spite of this, the resulting cranial ganglia, craniofacial skeleton, and heart developed normally when neural crest cells lacked DNMT3b. This indicates that DNTM3b is not necessary in cranial neural crest cells for their development. We conclude that defects in neural crest derivatives in DNMT3b mutant mice reflect a requirement for DNMT3b in lineages such as the branchial arch mesendoderm or the cardiac mesoderm that interact with neural crest cells during formation of these structures.

  10. Architecture of Human Language from the Perspective of a Case of Childhood Aphasia — Landau–Kleffner Syndrome

    Directory of Open Access Journals (Sweden)

    Koji Hoshi

    2016-12-01

    Full Text Available This paper addresses Landau–Kleffner syndrome (LKS, a childhood aphasia, from the perspective of I-language and the critical period for first language acquisition. LKS involves a language disorder and behavioral disturbances resembling autistic spectrum disorders due to electroencephalographic abnormalities with continuous spike-and-waves during sleep over the temporal regions. Comparing LKS with other childhood syndromes, the architecture of language is explored through elucidating the linguistic mechanisms behind the language disorder in LKS on the basis of Hickok & Poeppel’s (2007 dual-stream model of speech processing. It is claimed that early onset LKS provides further support for the critical period for first language acquisition and modularity of mind (the faculty of language, and that verbal auditory input during the critical period is most crucial for language recovery and development in LKS. Considering that electroencephalographic abnormalities affect cognitive/motor functions, ameliorating neural dysfunction in the affected brain areas with proper application of trans-cranial direct current stimulation is recommended.

  11. Adult Mammalian Neural Stem Cells and Neurogenesis: Five Decades Later

    Science.gov (United States)

    Bond, Allison M.; Ming, Guo-li; Song, Hongjun

    2015-01-01

    Summary Adult somatic stem cells in various organs maintain homeostatic tissue regeneration and enhance plasticity. Since its initial discovery five decades ago, investigations of adult neurogenesis and neural stem cells have led to an established and expanding field that has significantly influenced many facets of neuroscience, developmental biology and regenerative medicine. Here we review recent progress and focus on questions related to adult mammalian neural stem cells that also apply to other somatic stem cells. We further discuss emerging topics that are guiding the field toward better understanding adult neural stem cells and ultimately applying these principles to improve human health. PMID:26431181

  12. Central neural pathways for thermoregulation

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    Morrison, Shaun F.; Nakamura, Kazuhiro

    2010-01-01

    Central neural circuits orchestrate a homeostatic repertoire to maintain body temperature during environmental temperature challenges and to alter body temperature during the inflammatory response. This review summarizes the functional organization of the neural pathways through which cutaneous thermal receptors alter thermoregulatory effectors: the cutaneous circulation for heat loss, the brown adipose tissue, skeletal muscle and heart for thermogenesis and species-dependent mechanisms (sweating, panting and saliva spreading) for evaporative heat loss. These effectors are regulated by parallel but distinct, effector-specific neural pathways that share a common peripheral thermal sensory input. The thermal afferent circuits include cutaneous thermal receptors, spinal dorsal horn neurons and lateral parabrachial nucleus neurons projecting to the preoptic area to influence warm-sensitive, inhibitory output neurons which control thermogenesis-promoting neurons in the dorsomedial hypothalamus that project to premotor neurons in the rostral ventromedial medulla, including the raphe pallidus, that descend to provide the excitation necessary to drive thermogenic thermal effectors. A distinct population of warm-sensitive preoptic neurons controls heat loss through an inhibitory input to raphe pallidus neurons controlling cutaneous vasoconstriction. PMID:21196160

  13. Congenital Unilateral Deafness Affects Cerebral Organization of Reading

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    Alice Mado Proverbio

    2013-06-01

    Full Text Available It is known that early sensory deprivation modifies brain functional structure and connectivity. The aim of the present study was to investigate the neuro-functional organization of reading in a patient with profound congenital unilateral deafness. Using event-related potentials (ERPs, we compared cortical networks supporting the processing of written words in patient RA (completely deaf in the right ear since birth and in a group of control volunteers. We found that congenital unilateral hearing deprivation modifies neural mechanisms of word reading. Indeed, while written word processing was left-lateralized in controls, we found a strong right lateralization of the fusiform and inferior occipital gyri activation in RA. This finding goes in the same direction of recent proposals that the ventral occipito-temporal activity in word reading seem to lateralize to the same hemisphere as the one involved in spoken language processing.

  14. Face recognition: a convolutional neural-network approach.

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    Lawrence, S; Giles, C L; Tsoi, A C; Back, A D

    1997-01-01

    We present a hybrid neural-network for human face recognition which compares favourably with other methods. The system combines local image sampling, a self-organizing map (SOM) neural network, and a convolutional neural network. The SOM provides a quantization of the image samples into a topological space where inputs that are nearby in the original space are also nearby in the output space, thereby providing dimensionality reduction and invariance to minor changes in the image sample, and the convolutional neural network provides partial invariance to translation, rotation, scale, and deformation. The convolutional network extracts successively larger features in a hierarchical set of layers. We present results using the Karhunen-Loeve transform in place of the SOM, and a multilayer perceptron (MLP) in place of the convolutional network for comparison. We use a database of 400 images of 40 individuals which contains quite a high degree of variability in expression, pose, and facial details. We analyze the computational complexity and discuss how new classes could be added to the trained recognizer.

  15. Language structure is partly determined by social structure.

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    Gary Lupyan

    Full Text Available BACKGROUND: Languages differ greatly both in their syntactic and morphological systems and in the social environments in which they exist. We challenge the view that language grammars are unrelated to social environments in which they are learned and used. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a statistical analysis of >2,000 languages using a combination of demographic sources and the World Atlas of Language Structures--a database of structural language properties. We found strong relationships between linguistic factors related to morphological complexity, and demographic/socio-historical factors such as the number of language users, geographic spread, and degree of language contact. The analyses suggest that languages spoken by large groups have simpler inflectional morphology than languages spoken by smaller groups as measured on a variety of factors such as case systems and complexity of conjugations. Additionally, languages spoken by large groups are much more likely to use lexical strategies in place of inflectional morphology to encode evidentiality, negation, aspect, and possession. Our findings indicate that just as biological organisms are shaped by ecological niches, language structures appear to adapt to the environment (niche in which they are being learned and used. As adults learn a language, features that are difficult for them to acquire, are less likely to be passed on to subsequent learners. Languages used for communication in large groups that include adult learners appear to have been subjected to such selection. Conversely, the morphological complexity common to languages used in small groups increases redundancy which may facilitate language learning by infants. CONCLUSIONS/SIGNIFICANCE: We hypothesize that language structures are subjected to different evolutionary pressures in different social environments. Just as biological organisms are shaped by ecological niches, language structures appear to adapt to the

  16. Optimizing estimation of hemispheric dominance for language using magnetic source imaging.

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    Passaro, Antony D; Rezaie, Roozbeh; Moser, Dana C; Li, Zhimin; Dias, Nadeeka; Papanicolaou, Andrew C

    2011-10-06

    The efficacy of magnetoencephalography (MEG) as an alternative to invasive methods for investigating the cortical representation of language has been explored in several studies. Recently, studies comparing MEG to the gold standard Wada procedure have found inconsistent and often less-than accurate estimates of laterality across various MEG studies. Here we attempted to address this issue among normal right-handed adults (N=12) by supplementing a well-established MEG protocol involving word recognition and the single dipole method with a sentence comprehension task and a beamformer approach localizing neural oscillations. Beamformer analysis of word recognition and sentence comprehension tasks revealed a desynchronization in the 10-18Hz range, localized to the temporo-parietal cortices. Inspection of individual profiles of localized desynchronization (10-18Hz) revealed left hemispheric dominance in 91.7% and 83.3% of individuals during the word recognition and sentence comprehension tasks, respectively. In contrast, single dipole analysis yielded lower estimates, such that activity in temporal language regions was left-lateralized in 66.7% and 58.3% of individuals during word recognition and sentence comprehension, respectively. The results obtained from the word recognition task and localization of oscillatory activity using a beamformer appear to be in line with general estimates of left hemispheric dominance for language in normal right-handed individuals. Furthermore, the current findings support the growing notion that changes in neural oscillations underlie critical components of linguistic processing. Published by Elsevier B.V.

  17. Neural networks and applications tutorial

    Science.gov (United States)

    Guyon, I.

    1991-09-01

    The importance of neural networks has grown dramatically during this decade. While only a few years ago they were primarily of academic interest, now dozens of companies and many universities are investigating the potential use of these systems and products are beginning to appear. The idea of building a machine whose architecture is inspired by that of the brain has roots which go far back in history. Nowadays, technological advances of computers and the availability of custom integrated circuits, permit simulations of hundreds or even thousands of neurons. In conjunction, the growing interest in learning machines, non-linear dynamics and parallel computation spurred renewed attention in artificial neural networks. Many tentative applications have been proposed, including decision systems (associative memories, classifiers, data compressors and optimizers), or parametric models for signal processing purposes (system identification, automatic control, noise canceling, etc.). While they do not always outperform standard methods, neural network approaches are already used in some real world applications for pattern recognition and signal processing tasks. The tutorial is divided into six lectures, that where presented at the Third Graduate Summer Course on Computational Physics (September 3-7, 1990) on Parallel Architectures and Applications, organized by the European Physical Society: (1) Introduction: machine learning and biological computation. (2) Adaptive artificial neurons (perceptron, ADALINE, sigmoid units, etc.): learning rules and implementations. (3) Neural network systems: architectures, learning algorithms. (4) Applications: pattern recognition, signal processing, etc. (5) Elements of learning theory: how to build networks which generalize. (6) A case study: a neural network for on-line recognition of handwritten alphanumeric characters.

  18. Anosmin-1 is essential for neural crest and cranial placodes formation in Xenopus.

    Science.gov (United States)

    Bae, Chang-Joon; Hong, Chang-Soo; Saint-Jeannet, Jean-Pierre

    2018-01-15

    During embryogenesis vertebrates develop a complex craniofacial skeleton associated with sensory organs. These structures are primarily derived from two embryonic cell populations the neural crest and cranial placodes, respectively. Neural crest cells and cranial placodes are specified through the integrated action of several families of signaling molecules, and the subsequent activation of a complex network of transcription factors. Here we describe the expression and function of Anosmin-1 (Anos1), an extracellular matrix protein, during neural crest and cranial placodes development in Xenopus laevis. Anos1 was identified as a target of Pax3 and Zic1, two transcription factors necessary and sufficient to generate neural crest and cranial placodes. Anos1 is expressed in cranial neural crest progenitors at early neurula stage and in cranial placode derivatives later in development. We show that Anos1 function is required for neural crest and sensory organs development in Xenopus, consistent with the defects observed in Kallmann syndrome patients carrying a mutation in ANOS1. These findings indicate that anos1 has a conserved function in the development of craniofacial structures, and indicate that anos1-depleted Xenopus embryos represent a useful model to analyze the pathogenesis of Kallmann syndrome. Copyright © 2017. Published by Elsevier Inc.

  19. Detecting insider threats to organizations through language change

    NARCIS (Netherlands)

    Taylor, Paul J; Dando, C.; Omerod, T.; Ball, L.; Jenkins, M.; Sandham, A.; Menacere, T

    2013-01-01

    The act of conducting an insider attack carries with it cognitive and social challenges that may affect an offender’s day-to-day work behavior. We test this hypothesis by examining the language used in e-mails that were sent as part of a 6-hr workplace simulation. The simulation involved

  20. Altered Neural Activity during Irony Comprehension in Unaffected First-Degree Relatives of Schizophrenia Patients—An fMRI Study

    Directory of Open Access Journals (Sweden)

    Róbert Herold

    2018-01-01

    Full Text Available Irony is a type of figurative language in which the literal meaning of the expression is the opposite of what the speaker intends to communicate. Even though schizophrenic patients are known as typically impaired in irony comprehension and in the underlying neural functions, to date no one has explored the neural correlates of figurative language comprehension in first-degree relatives of schizophrenic patients. In the present study, we examined the neural correlates of irony understanding in schizophrenic patients and in unaffected first-degree relatives of patients compared to healthy adults with functional MRI. Our aim was to investigate if possible alterations of the neural circuits supporting irony comprehension in first-degree relatives of patients with schizophrenia would fulfill the familiality criterion of an endophenotype. We examined 12 schizophrenic patients, 12 first-degree relatives of schizophrenia patients and 12 healthy controls with functional MRI while they were performing irony and control tasks. Different phases of irony processing were examined, such as context processing and ironic statement comprehension. Patients had significantly more difficulty understanding irony than controls or relatives. Patients also showed markedly different neural activation pattern compared to controls in both stages of irony processing. Although no significant differences were found in the performance of the irony tasks between the control group and the relative group, during the fMRI analysis, the relatives showed stronger brain activity in the left dorsolateral prefrontal cortex during the context processing phase of irony tasks than the control group. However, the controls demonstrated higher activations in the left dorsomedial prefrontal cortex and in the right inferior frontal gyrus during the ironic statement phase of the irony tasks than the relative group. Our results show that despite good task performance, first-degree relatives of