scholarly journals Neural harmonics reflect grammaticality

2020 ◽  
Author(s):  
Alessandro Tavano ◽  
Stefan Blohm ◽  
Christine Knoop ◽  
R Muralikrishnan ◽  
Mathias Scharinger ◽  
...  
Keyword(s):  
Neural Activity ◽  
Syntactic Structure ◽  
Attention Capture ◽  
External Stimulus ◽  
Harmonic Structure ◽  
Stimulus Rate ◽  
Structure Building ◽  
Grammatical Sensitivity ◽  
Direct Reflection ◽  
Better Than

AbstractCan neural activity reveal syntactic structure building processes and their violations? To verify this, we recorded electroencephalographic and behavioral data as participants discriminated concatenated isochronous sentence chains containing only grammatical sentences (regular trials) from those containing ungrammatical sentences (irregular trials). We found that the repetition of abstract syntactic categories generates a harmonic structure of their period independently of stimulus rate, thereby separating endogenous from exogenous neural rhythms. Behavioral analyses confirmed this dissociation. Internal neural harmonics extracted from regular trials predicted participants’ grammatical sensitivity better than harmonics extracted from irregular trials, suggesting a direct reflection of grammatical sensitivity. Instead, entraining to external stimulus rate scaled with task sensitivity only when extracted from irregular trials, reflecting attention-capture processing. Neural harmonics to repeated syntactic categories constitute the first behaviorally relevant, purely internal index of syntactic competence.

Early emergence of syntactic awareness and cross-linguistic influence in bilingual children’s judgments

2011 ◽  
Vol 15 (4) ◽  
pp. 521-534 ◽  
Author(s):  
Cassandra Foursha-Stevenson ◽  
Elena Nicoladis
Keyword(s):  
Syntactic Structure ◽  
Language Choice ◽  
Preschool Age ◽  
Bilingual Children ◽  
Metalinguistic Awareness ◽  
Syntactic Awareness ◽  
Grammaticality Judgment ◽  
English Bilingual ◽  
French And English ◽  
Better Than

Bilingual children sometimes perform better than same-aged monolingual children on metalinguistic awareness tasks, such as a grammaticality judgment. Some of these differences can be attributed to bilinguals having to learn to control attention to language choice. This study tested the hypothesis that bilingual children, as young as preschool age, would score overall higher than monolingual children on a grammaticality judgment test. French–English bilingual preschoolers judged the acceptability of three constructions in French and English (i.e. adjective–noun ordering, obligatoriness of a determiner, and object pronoun placement). Their performance was compared with that of a group of age-matched English monolinguals. The results showed that the bilingual children scored higher than the monolingual children. These results demonstrate that syntactic awareness develops quite early for bilinguals. Additionally, the bilingual children demonstrated cross-linguistic influence of core syntactic structure in French, as their judgments were affected by English acceptability.

scholarly journals Learning Improved Semantic Representations with Tree-Structured LSTM for Hashtag Recommendation: An Experimental Study

Information ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 127 ◽  
Author(s):  
Rui Zhu ◽  
Delu Yang ◽  
Yang Li
Keyword(s):  
Deep Neural Networks ◽  
Semantic Information ◽  
Syntactic Structure ◽  
Text Representation ◽  
Neural Models ◽  
Textual Features ◽  
Real World Datasets ◽  
Core Idea ◽  
Significant Attention ◽  
Better Than

A hashtag is a type of metadata tag used on social networks, such as Twitter and other microblogging services. Hashtags indicate the core idea of a microblog post and can help people to search for specific themes or content. However, not everyone tags their posts themselves. Therefore, the task of hashtag recommendation has received significant attention in recent years. To solve the task, a key problem is how to effectively represent the text of a microblog post in a way that its representation can be utilized for hashtag recommendation. We study two major kinds of text representation methods for hashtag recommendation, including shallow textual features and deep textual features learned by deep neural models. Most existing work tries to use deep neural networks to learn microblog post representation based on the semantic combination of words. In this paper, we propose to adopt Tree-LSTM to improve the representation by combining the syntactic structure and the semantic information of words. We conduct extensive experiments on two real world datasets. The experimental results show that deep neural models generally perform better than traditional methods. Specially, Tree-LSTM achieves significantly better results on hashtag recommendation than standard LSTM, with a 30% increase in F1-score, which indicates that it is promising to utilize syntactic structure in the task of hashtag recommendation.

The Effect of Modulation and Formal Manipulation on Perception of Tonic Closure by Expert Listeners

1999 ◽  
Vol 16 (4) ◽  
pp. 389-407 ◽  
Author(s):  
Elizabeth West Marvin ◽  
Alexander Brinkman
Keyword(s):  
Original Composition ◽  
Harmonic Structure ◽  
Orchestral Works ◽  
Trial Participants ◽  
Better Than

This study arises in response to previous research that calls into question the ability of musically trained listeners to perceive tonal closure in the original tonic key. In our Experiment 1, 36 experienced musicians heard 12 randomly ordered excerpts from piano and orchestral works in three categories: nonmodulating, modulating to the dominant, modulating to a key other than the dominant. After hearing each excerpt, participants answered six questions, one of which asked whether the concluding key was the same as the initial one. Participants correctly answered this question at above-chance levels, with music academics (theorists and musicologists) more accurate than other musicians. In Experiment 2, 33 experienced musicians heard MIDI performances of six Handel keyboard compositions. On each trial, participants heard either the original composition or one of two variants with phrase units rearranged. Trials were quasi-randomly ordered so that an original and variant were not heard in succession. Three types of tonal motion resulted from our formal manipulation: the stimulus began and ended in the tonic key, began and ended in the dominant key, or began and ended in different keys. After hearing each work, participants answered seven questions, of which data were analyzed for three: whether the beginning and ending key were the same, whether the harmonic structure conformed to stylistic expectations, and whether the final key was the tonic. Participants' accuracy on the beginning/ending key question was no better than chance would predict; however, listeners were able to discriminate between works that ended in the tonic key and those that did not. Unlike Experiment 1, we found no significant differences in accuracy between music academics and other musicians. Listeners generally found both the original and the manipulated compositions to conform to stylistic expectations, possibly because they attended to local harmonic relationships rather than global ones.

scholarly journals DIBERT: Dependency Injected Bidirectional Encoder Representations from Transformers

2021 ◽  
Author(s):  
Abdul Wahab ◽  
Rafet Sifa
Keyword(s):  
Natural Language ◽  
Sentiment Analysis ◽  
Semantic Similarity ◽  
Syntactic Structure ◽  
Language Modeling ◽  
Benchmark Dataset ◽  
Fine Tuning ◽  
New Model ◽  
Dependency Tree ◽  
Better Than

<div> <div> <div> <p> </p><div> <div> <div> <p>In this paper, we propose a new model named DIBERT which stands for Dependency Injected Bidirectional Encoder Representations from Transformers. DIBERT is a variation of the BERT and has an additional third objective called Parent Prediction (PP) apart from Masked Language Modeling (MLM) and Next Sentence Prediction (NSP). PP injects the syntactic structure of a dependency tree while pre-training the DIBERT which generates syntax-aware generic representations. We use the WikiText-103 benchmark dataset to pre-train both BERT- Base and DIBERT. After fine-tuning, we observe that DIBERT performs better than BERT-Base on various downstream tasks including Semantic Similarity, Natural Language Inference and Sentiment Analysis. </p> </div> </div> </div> </div> </div> </div>

scholarly journals DIBERT: Dependency Injected Bidirectional Encoder Representations from Transformers

2021 ◽  
Author(s):  
Abdul Wahab ◽  
Rafet Sifa
Keyword(s):  
Natural Language ◽  
Sentiment Analysis ◽  
Semantic Similarity ◽  
Syntactic Structure ◽  
Language Modeling ◽  
Benchmark Dataset ◽  
Fine Tuning ◽  
New Model ◽  
Dependency Tree ◽  
Better Than

<div> <div> <div> <p> </p><div> <div> <div> <p>In this paper, we propose a new model named DIBERT which stands for Dependency Injected Bidirectional Encoder Representations from Transformers. DIBERT is a variation of the BERT and has an additional third objective called Parent Prediction (PP) apart from Masked Language Modeling (MLM) and Next Sentence Prediction (NSP). PP injects the syntactic structure of a dependency tree while pre-training the DIBERT which generates syntax-aware generic representations. We use the WikiText-103 benchmark dataset to pre-train both BERT- Base and DIBERT. After fine-tuning, we observe that DIBERT performs better than BERT-Base on various downstream tasks including Semantic Similarity, Natural Language Inference and Sentiment Analysis. </p> </div> </div> </div> </div> </div> </div>

scholarly journals CORRECTIVE FEEDBACK AND WRITING ACCURACY OF STUDENTS ACROSS DIFFERENT LEVELS OF GRAMMATICAL SENSITIVITY

2016 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ayu Rizki Septiana ◽  
Gunadi Harry Sulistyo ◽  
A. Effendi Kadarisman
Keyword(s):  
Corrective Feedback ◽  
State University ◽  
Significant Difference ◽  
Grammatical Sensitivity ◽  
Writing Accuracy ◽  
Parametric Statistical Test ◽  
High Level ◽  
And Control ◽  
Experimental Group ◽  
Better Than

<span>This study investigates whether indirect corrective feedback is effective o<span>n students’ writing <span>accuracy and whether there is any interaction between corrective feedback and students’ levels of <span>grammatical sensitivity. A quasi-factorial design was adopted for this research. The subjects of the <span>study were fourth-semester students of English Department, at a State University in Malang, selected <span>randomly. The experimental group was treated with indirect corrective feedback and the control <span>group with direct corrective feedback. A parametric statistical test, ANCOVA, was used to test the <span>hypotheses. The findings show that there was no statistical difference on writing accuracy between <span>the experimental and control groups. Yet, among students with a high level of grammatical <span>sensitivity, there was significant difference in writing accuracy between those given indirect and <span>direct corrective feedback. Further, there was no interaction between corrective feedback on writing <span>accuracy and students’ levels of grammatical sensitivity. However, indirect corrective feedback <span>improved students’ writi<span>ng accuracy better than direct corrective feedback.</span></span></span></span></span></span></span></span></span></span></span><br /></span></span></span>

Susceptibility to interference: underlying mechanisms, and implications for prediction

2016 ◽  
Vol 20 (4) ◽  
pp. 696-697 ◽  
Author(s):  
EDITH KAAN
Keyword(s):  
Language Processing ◽  
Sentence Processing ◽  
Syntactic Structure ◽  
Syntactic Processing ◽  
Healthy Young Adult ◽  
Aging Research ◽  
Structure Building ◽  
L2 Processing ◽  
Underlying Mechanisms ◽  
Increased Susceptibility

Over the years, models proposed for second-language (L2) processing have been remarkably parallel to those proposed for Broca's aphasia. Differences between agrammatic and unaffected language processing have been explained, e.g., in terms of lack of detailed syntactic structure building (Grodzinsky, 1995), resource deficits (Haarman, Just & Carpenter, 1997), slow syntactic processing (Burkhardt, Avrutin, Piñango & Ruigendijk, 2008), or slowed lexical access (Love, Swinney, Walenski & Zurif, 2008). Each of these approaches have their homolog in L2 processing (e.g., Clahsen & Felser, 2006; McDonald, 2006; Dekydtspotter, Schwartz & Sprouse, 2006; Hopp, 2013, respectively). It is therefore not surprising that Cunnings's proposal (Cunnings, 2016) parallels another idea in aphasia and aging research, namely that deviations from healthy young adult monolingual sentence processing can be attributed to an increased susceptibility to interference (e.g., Sheppard, Walenski, Love & Shapiro, 2015).

scholarly journals When Events Change Their Nature: The Neurocognitive Mechanisms Underlying Aspectual Coercion

2014 ◽  
Vol 26 (9) ◽  
pp. 1905-1917 ◽  
Author(s):  
Martin Paczynski ◽  
Ray Jackendoff ◽  
Gina Kuperberg
Keyword(s):  
Neural Activity ◽  
Semantic Processing ◽  
Time Course ◽  
Late Onset ◽  
Syntactic Structure ◽  
World Knowledge ◽  
Event Representation ◽  
Scalp Distribution ◽  
Context Type ◽  
Aspectual Coercion

The verb “pounce” describes a single, near-instantaneous event. Yet, we easily understand that, “For several minutes the cat pounced…” describes a situation in which multiple pounces occurred, although this interpretation is not overtly specified by the sentence's syntactic structure or by any of its individual words—a phenomenon known as “aspectual coercion.” Previous psycholinguistic studies have reported processing costs in association with aspectual coercion, but the neurocognitive mechanisms giving rise to these costs remain contentious. Additionally, there is some controversy about whether readers commit to a full interpretation of the event when the aspectual information becomes available, or whether they leave it temporarily underspecified until later in the sentence. Using ERPs, we addressed these questions in a design that fully crossed context type (punctive, durative, frequentative) with verb type (punctive, durative). We found a late, sustained negativity to punctive verbs in durative contexts, but not in frequentative (e.g., explicitly iterative) contexts. This effect was distinct from the N400 in both its time course and scalp distribution, suggesting that it reflected a different underlying neurocognitive mechanism. We also found that ERPs to durative verbs were unaffected by context type. Together, our results provide strong evidence that neural activity associated with aspectual coercion is driven by the engagement of a morphosyntactically unrealized semantic operator rather than by violations of real-world knowledge, more general shifts in event representation, or event iterativity itself. More generally, our results add to a growing body of evidence that a set of late-onset sustained negativities reflect elaborative semantic processing that goes beyond simply combining the meaning of individual words with syntactic structure to arrive at a final representation of meaning.

scholarly journals Reminders of past choices bias decisions for reward in humans

2015 ◽  
Author(s):  
Aaron M. Bornstein ◽  
Mel W. Khaw ◽  
Daphna Shohamy ◽  
Nathaniel D. Daw
Keyword(s):  
Neural Activity ◽  
Incremental Learning ◽  
Strong Influence ◽  
Empirical Support ◽  
Decision Time ◽  
Choice Task ◽  
Neural Mechanisms ◽  
Sampling Process ◽  
Past Experiences ◽  
Better Than

AbstractWe provide evidence that decisions are made by consulting memories for individual past experiences, and that this process can be biased in favor of past choices using incidental reminders. First, in a standard rewarded choice task, we show that a model that estimates value at decision-time using individual samples of past outcomes fits choices and decision-related neural activity better than a canonical incremental learning model. In a second experiment, we bias this sampling process by incidentally reminding participants of individual past decisions. The next decision after a reminder shows a strong influence of the action taken and value received on the reminded trial. These results provide new empirical support for a decision architecture that relies on samples of individual past choice episodes rather than incrementally averaged rewards in evaluating options, and has suggestive implications for the underlying cognitive and neural mechanisms.

scholarly journals What Neural Oscillations Can(not) Do for Syntactic Structure Building

2021 ◽  
Author(s):  
Nina Kazanina ◽  
Alessandro Tavano
Keyword(s):  
Information Integration ◽  
Syntactic Structure ◽  
Neural Mechanisms ◽  
Neural Oscillations ◽  
Multi Scale ◽  
Structure Building ◽  
Exact Function ◽  
Starting Point ◽  
Hierarchical Nature ◽  
Neurophysiological Basis

Understanding what someone says requires relating words in the sentence to one another as instructed by grammatical rules of language. In recent years, a neurophysiological basis for this process has become a prominent topic of discussion in cognitive neuroscience. Current proposals about the neural mechanisms of syntactic structure building converge in assigning a key role to neural oscillations but differ in the exact function assigned to them. We discuss two types of approaches – oscillations for chunking and oscillations for multi-scale information integration – and evaluate their merits and limitations considering a fundamentally hierarchical nature of syntactic representations in natural language. We highlight insights that can provide a tangible starting point for a wide-scope neurocognitive model of syntactic structure building.

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