scholarly journals Neural evidence for representationally specific prediction in language processing

2018 ◽  
Author(s):  
Lin Wang ◽  
Gina Kuperberg ◽  
Ole Jensen
Keyword(s):  
Language Processing ◽  
Language Comprehension ◽  
Sensory Input ◽  
Brain Activity ◽  
Temporal Region ◽  
Semantic Representations ◽  
Spatial And Temporal Patterns ◽  
Final Word ◽  
Specific Prediction ◽  
The Brain

AbstractPrevious studies suggest that people generate predictions during language comprehension at multiple linguistic levels. It has been hypothesized that, under some circumstances, this can result in the pre-activation of specific lexico-semantic representations. We asked whether such representationally specific semantic pre-activation can be detected in the brain ahead of encountering bottom-up input. We measured MEG activity as participants read highly constraining sentences in which the final word could be predicted. We found that both spatial and temporal patterns of the brain activity prior to the onset of this word were more similar when the same words were predicted than when different words were predicted. This pre-activation was transient and engaged a left inferior and medial temporal region. These results suggest that unique spatial patterns of neural activity associated with the pre-activation of distributed semantic representations can be detected prior to the appearance of new sensory input, and that the left inferior and medial temporal regions may play a role in temporally binding such representations, giving rise to specific lexico-semantic predictions.

scholarly journals Task-Dependent Warping of Semantic Representations During Search for Visual Action Categories

2021 ◽  
Author(s):  
Mo Shahdloo ◽  
Emin Çelik ◽  
Burcu A Urgen ◽  
Jack L. Gallant ◽  
Tolga Çukur
Keyword(s):  
Visual Search ◽  
Social Interactions ◽  
Brain Activity ◽  
Semantic Representation ◽  
Natural Scenes ◽  
Action Perception ◽  
Semantic Representations ◽  
Object Categories ◽  
Search For Objects ◽  
The Brain

Object and action perception in cluttered dynamic natural scenes relies on efficient allocation of limited brain resources to prioritize the attended targets over distractors. It has been suggested that during visual search for objects, distributed semantic representation of hundreds of object categories is warped to expand the representation of targets. Yet, little is known about whether and where in the brain visual search for action categories modulates semantic representations. To address this fundamental question, we studied human brain activity recorded via functional magnetic resonance imaging while subjects viewed natural movies and searched for either communication or locomotion actions. We find that attention directed to action categories elicits tuning shifts that warp semantic representations broadly across neocortex, and that these shifts interact with intrinsic selectivity of cortical voxels for target actions. These results suggest that attention serves to facilitate task performance during social interactions by dynamically shifting semantic selectivity towards target actions, and that tuning shifts are a general feature of conceptual representations in the brain.

scholarly journals Searching through functional space reveals distributed visual, auditory, and semantic coding in the human brain

2020 ◽  
Author(s):  
Sreejan Kumar ◽  
Cameron T. Ellis ◽  
Thomas O’Connell ◽  
Marvin M Chun ◽  
Nicholas B. Turk-Browne
Keyword(s):  
Human Brain ◽  
Language Processing ◽  
Brain Function ◽  
Computational Models ◽  
Brain Activity ◽  
Functional Space ◽  
Semantic Features ◽  
Brain Functions ◽  
Auditory Features ◽  
The Brain

AbstractThe extent to which brain functions are localized or distributed is a foundational question in neuroscience. In the human brain, common fMRI methods such as cluster correction, atlas parcellation, and anatomical searchlight are biased by design toward finding localized representations. Here we introduce the functional searchlight approach as an alternative to anatomical searchlight analysis, the most commonly used exploratory multivariate fMRI technique. Functional searchlight removes any anatomical bias by grouping voxels based only on functional similarity and ignoring anatomical proximity. We report evidence that visual and auditory features from deep neural networks and semantic features from a natural language processing model are more widely distributed across the brain than previously acknowledged. This approach provides a new way to evaluate and constrain computational models with brain activity and pushes our understanding of human brain function further along the spectrum from strict modularity toward distributed representation.

scholarly journals Sensory-modality independent activation of the brain network for language

2019 ◽  
Author(s):  
Sophie Arana ◽  
André Marquand ◽  
Annika Hultén ◽  
Peter Hagoort ◽  
Jan-Mathijs Schoffelen
Keyword(s):  
Language Processing ◽  
Sentence Processing ◽  
Human Subjects ◽  
Brain Activity ◽  
Activity Patterns ◽  
Sensory Modality ◽  
Brain Network ◽  
Large Network ◽  
Individual Subject ◽  
The Brain

AbstractThe meaning of a sentence can be understood, whether presented in written or spoken form. Therefore it is highly probable that brain processes supporting language comprehension are at least partly independent of sensory modality. To identify where and when in the brain language processing is independent of sensory modality, we directly compared neuromagnetic brain signals of 200 human subjects (102 males) either reading or listening to sentences. We used multiset canonical correlation analysis to align individual subject data in a way that boosts those aspects of the signal that are common to all, allowing us to capture word-by-word signal variations, consistent across subjects and at a fine temporal scale. Quantifying this consistency in activation across both reading and listening tasks revealed a mostly left hemispheric cortical network. Areas showing consistent activity patterns include not only areas previously implicated in higher-level language processing, such as left prefrontal, superior & middle temporal areas and anterior temporal lobe, but also parts of the control-network as well as subcentral and more posterior temporal-parietal areas. Activity in this supramodal sentence processing network starts in temporal areas and rapidly spreads to the other regions involved. The findings do not only indicate the involvement of a large network of brain areas in supramodal language processing, but also indicate that the linguistic information contained in the unfolding sentences modulates brain activity in a word-specific manner across subjects.

scholarly journals Insights into Early Word Comprehension: Tracking the Neural Representations of Word Semantics in Infants.

2021 ◽  
Author(s):  
Rohan Saha ◽  
Jennifer Campbell ◽  
Janet F. Werker ◽  
Alona Fyshe
Keyword(s):  
Brain Activity ◽  
Word Meaning ◽  
Age Groups ◽  
Event Related Potential ◽  
Neural Representation ◽  
Machine Learning Techniques ◽  
Semantic Representations ◽  
Word Comprehension ◽  
Neural Representations ◽  
The Brain

Infants start developing rudimentary language skills and can start understanding simple words well before their first birthday. This development has also been shown primarily using Event Related Potential (ERP) techniques to find evidence of word comprehension in the infant brain. While these works validate the presence of semantic representations of words (word meaning) in infants, they do not tell us about the mental processes involved in the manifestation of these semantic representations or the content of the representations. To this end, we use a decoding approach where we employ machine learning techniques on Electroencephalography (EEG) data to predict the semantic representations of words found in the brain activity of infants. We perform multiple analyses to explore word semantic representations in two groups of infants (9-month-old and 12-month-old). Our analyses show significantly above chance decodability of overall word semantics, word animacy, and word phonetics. As we analyze brain activity, we observe that participants in both age groups show signs of word comprehension immediately after word onset, marked by our model's significantly above chance word prediction accuracy. We also observed strong neural representations of word phonetics in the brain data for both age groups, some likely correlated to word decoding accuracy and others not. Lastly, we discover that the neural representations of word semantics are similar in both infant age groups. Our results on word semantics, phonetics, and animacy decodability, give us insights into the evolution of neural representation of word meaning in infants.

scholarly journals Pragmatic Language Processing in the Adolescent Brain

2019 ◽  
Author(s):  
Salomi S. Asaridou ◽  
Ö. Ece Demir-Lira ◽  
Julia Uddén ◽  
Susan Goldin-Meadow ◽  
Steven L. Small
Keyword(s):  
Social Interactions ◽  
Cognitive Processing ◽  
Language Processing ◽  
Language Comprehension ◽  
Social Contexts ◽  
Pragmatic Competence ◽  
Pragmatic Language ◽  
Typically Developing ◽  
The Brain ◽  
Preceding Question

Adolescence is a developmental period in which social interactions become increasingly important. Successful social interactions rely heavily on pragmatic competence, the appropriate use of language in different social contexts, a skill that is still developing in adolescence. In the present study, we used fMRI to characterize the brain networks underlying pragmatic language processing in typically developing adolescents. We used an indirect speech paradigm whereby participants were presented with question/answer dialogues in which the meaning of the answer had to be inferred from the context, in this case the preceding question. Participants were presented with three types of answers: (1) direct replies, i.e., simple answers to open-ended questions, (2) indirect informative replies, i.e., answers in which the speaker’s intention was to add more information to a yes/no question, and (3) indirect affective replies, i.e., answers in which the speaker’s intention was to express polite refusals, negative opinions or to save face in response to an emotionally charged question. We found that indirect affective replies elicited the strongest response in brain areas associated with language comprehension (superior temporal gyri), theory of mind (medial prefrontal cortex, temporo-parietal junction, and precuneus), and attention/working memory (inferior frontal gyri). The increased activation to indirect affective as opposed to indirect informative and direct replies potentially reflects the high salience of opinions and perspectives of others in adolescence. Our results add to previous findings on socio-cognitive processing in adolescents and extend them to pragmatic language comprehension.

Grammatical predictors for fMRI time-courses

2019 ◽  
pp. 159-173
Author(s):  
Jixing Li ◽  
John Hale
Keyword(s):  
Language Processing ◽  
Sentence Processing ◽  
Time Course ◽  
Temporal Region ◽  
Lexical Meaning ◽  
Word Sequence ◽  
Time Courses ◽  
Wernicke’S Area ◽  
Processing Effort ◽  
The Brain

This study examines several different time-series formalizations of sentence-processing effort, as regards their ability to predict the observed fMRI time-course in regions of the brain. These regressors formalize cognitive theories of language processing involving phrase structure parsing, memory burden, lexical meaning, and other factors such as word sequence probabilities. The results suggest that even in the presence of these covariates, a predictor based on minimalist grammars significantly improves a regression model of the BOLD signal in a posterior temporal region, roughly corresponding to Wernicke’s area.

scholarly journals Syntactic representations in the human brain: beyond effort-based metrics

2020 ◽  
Author(s):  
Aniketh Janardhan Reddy ◽  
Leila Wehbe
Keyword(s):  
Language Processing ◽  
Syntactic Structure ◽  
Brain Activity ◽  
Brain Regions ◽  
Syntactic Processing ◽  
Language System ◽  
Language Studies ◽  
Syntactic Information ◽  
Show Evidence ◽  
The Brain

AbstractWe are far from having a complete mechanistic understanding of the brain computations involved in language processing and of the role that syntax plays in those computations. Most language studies do not computationally model syntactic structure, and most studies that do model syntactic processing use effort-based metrics. These metrics capture the effort needed to process the syntactic information given by every word [9, 10, 25]. They can reveal where in the brain syntactic processing occurs, but not what features of syntax are processed by different brain regions. Here, we move beyond effort-based metrics and propose explicit features capturing the syntactic structure that is incrementally built while a sentence is being read. Using these features and functional Magnetic Resonance Imaging (fMRI) recordings of participants reading a natural text, we study the brain representation of syntax. We find that our syntactic structure-based features are better than effort-based metrics at predicting brain activity in various parts of the language system. We show evidence of the brain representation of complex syntactic information such as phrase and clause structures. We see that regions well-predicted by syntactic features are distributed in the language system and are not distinguishable from those processing semantics. Our results call for a shift in the approach used for studying syntactic processing.

Language Comprehension and Emotion

2019 ◽  
pp. 735-766
Author(s):  
Jos J. A. van Berkum
Keyword(s):  
Computational Complexity ◽  
Language Processing ◽  
Language Comprehension ◽  
Language Use ◽  
Human Cognition ◽  
Language Interpretation ◽  
The Brain

When you hear somebody speak, or read a bit of text, you are somehow assigning meaning to an unfolding sequence of signs. Because of the representational and computational complexity involved, this process of language interpretation is considered to be one of the major feats of human cognition. However, you also happen to be just another mammal, and as such, you are biologically predisposed to have emotions, evaluations, and moods (i.e. to feel certain things about your environment). How do these two acts of assigning meaning relate to one another? And what are the implications for neurolinguistics, the endeavor to understand how the brain realizes language use? After examining why emotion is not naturally foregrounded in language processing research, this chapter reviews some basic insights in emotion science, discusses a processing model of affective language comprehension, and explores how the model can contribute to neurolinguistics and other fields.

scholarly journals Representational pattern similarity of electrical brain activity reveals rapid and specific prediction during language comprehension

2020 ◽  
Author(s):  
Ryan J. Hubbard ◽  
Kara D. Federmeier
Keyword(s):  
Time Window ◽  
Brain Activity ◽  
Activity Patterns ◽  
Early Time ◽  
Final Word ◽  
Critical Function ◽  
Electrical Brain Activity ◽  
Pattern Similarity ◽  
Use Context ◽  
The Brain

AbstractPredicting upcoming stimuli and events is a critical function of the brain, and understanding the mechanisms of prediction has thus become a central topic in neuroscientific research. Language provides a fertile testing ground for examining predictive mechanisms, as comprehenders use context to predict different features of upcoming words. Although there is a substantive body of research on prediction in language, many aspects of the mechanisms of prediction remain elusive, in part due to a lack of methodological tools to probe prediction formation in the moment. To elucidate what features are neurally pre-activated and when, we used representational similarity analysis (RSA) on data from a sentence reading task (Federmeier et al., 2007). We compared EEG activity patterns elicited by expected and unexpected sentence final words to patterns from the preceding words of the sentence, in both strongly and weakly constraining sentences. Pattern similarity with the final word was increased in an early time window (suggestive of visual feature activation) following the presentation of the pre-final word, and this increase was modulated by both expectancy and constraint (greatest for strongly constrained expected words). This was not seen at earlier words, suggesting that predictions are precisely timed. Additionally, pre-final word activity – the predicted representation - had negative similarity with later final word activity, but only for strongly expected words. Together, these findings shed light on the mechanisms of prediction in the brain: features of upcoming stimuli are rapidly pre-activated following related cues, but the predicted information may receive reduced subsequent processing upon confirmation.

scholarly journals Efectos de una sesión de ejercicio físico sobre la actividad no lineal de las ondas cerebrales en estado basal (Effects of a physical exercise session on nonlinear activity of brainwaves at baseline)

Retos ◽  
2020 ◽  
pp. 180-187
Author(s):  
Fernando Maureira Cid ◽  
Elizabeth Flores Ferro ◽  
Hernan Díaz Muñoz ◽  
Helaine Barroso dos Reis ◽  
Carlos Rueff-Barroso ◽  
...  
Keyword(s):  
Physical Exercise ◽  
Brain Activity ◽  
Occipital Cortex ◽  
Exercise Session ◽  
Temporal Region ◽  
Theta Waves ◽  
Eyes Closed ◽  
Before And After ◽  
Brain Interface ◽  
The Brain

Introducción: en las últimas décadas el electroencefalograma se ha utilizado para estudiar los efectos del ejercicio físico sobre la actividad eléctrica cerebral, incluyendo nuevos paradigmas con matemáticas no lineales y teoría del caos. Material y método: El objetivo de la presente investigación fue determinar los efectos de 30 minutos de ejercicio físico aeróbico sobre la actividad neurofisiológica cerebral durante un estado basal. La muestra estuvo constituida por 13 varones voluntarios (siete experimentales y seis controles). El registro de la actividad cerebral (electroencefalografía) se realizó a través de un dispositivo cerebro-interfaz Emotiv Epoc® mientras los estudiantes permanecían dos minutos sentados con los ojos cerrados. Los registros se realizaron antes y después de un trabajo aeróbico de 30 minutos de trote. Resultados: las ondas delta presentan variaciones similares de los índices de Hurst entre sujetos del grupo control y experimental en las cortezas prefrontales temporales y occipitales, situación similar que ocurre con las ondas theta. Las ondas alfa resultan ser las más estables con pocas modificaciones entre la primera y segunda medición. Las ondas beta presentan variaciones similares en la región prefrontal y occipital entre el grupo control y experimental, pero en la región temporal existe mayor número de modificaciones en los sujetos que realizaron ejercicio físico. Las ondas gamma presentan mayor variabilidad en los sujetos controles con respecto a los experimentales. Conclusiones: Los índices de Hurst de las ondas delta, theta, alfa., beta y gamma de la corteza prefrontal, temporal y occipital en estado basal aumentan y disminuyen, sin encontrarse un patrón característico tras la intervención con ejercicio físico.Abstract. Introduction: In recent decades the electroencephalogram has been used to study the effects of physical exercise on brain electrical activity, including new paradigms with nonlinear mathematics and chaos theory. Material and method: The aim of this research was to determine the effects of 30 minutes of aerobic physical exercise on brain neurophysiological activity during at basal state. The sample consisted of 13 male volunteers (seven experimental and six controls).The recording of brain activity (electroencephalography) was performed through the brain-interface device Emotiv Epoc® while the students sat with their eyes closed for two minutes. The logs were performed before and after a 30-minute aerobic exercise.Results: delta waves show similar variations of Hurst indices between control and experimental group subjects in temporal and occipital prefrontal cortex, a similar situation as with theta waves. Alpha waves turn out to be the most stable with few modifications between the first and second measurements.The beta waves show similar variations in the prefrontal and occipital regions between the control and experimental groups, but in the temporal region there are more modifications in the subjects who performed physical exercise. Gamma waves show greater variability in control subjects compared to experimental ones.Conclusions: The Hurst indices of delta, theta, alpha, beta and gamma waves of the prefrontal, temporal and occipital cortex at baseline increase and decrease, without finding a characteristic pattern after intervention with physical exercise.

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