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Momenian M, Vaghefi M, Sadeghi H, Momtazi S, Meyer L. Language prediction in monolingual and bilingual speakers: an EEG study. Sci Rep 2024; 14:6818. [PMID: 38514713 PMCID: PMC10957906 DOI: 10.1038/s41598-024-57426-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 03/18/2024] [Indexed: 03/23/2024] Open
Abstract
Prediction of upcoming words is thought to be crucial for language comprehension. Here, we are asking whether bilingualism entails changes to the electrophysiological substrates of prediction. Prior findings leave it open whether monolingual and bilingual speakers predict upcoming words to the same extent and in the same manner. We address this issue with a naturalistic approach, employing an information-theoretic metric, surprisal, to predict and contrast the N400 brain potential in monolingual and bilingual speakers. We recruited 18 Iranian Azeri-Persian bilingual speakers and 22 Persian monolingual speakers. Subjects listened to a story in Persian while their electroencephalogram (EEG) was recorded. Bayesian item-level analysis was used. While in monolingual speakers N400 was sensitive to information-theoretic properties of both the current and previous words, in bilingual speakers N400 reflected the properties of the previous word only. Our findings show evidence for a processing delay in bilingual speakers which is consistent with prior research.
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Affiliation(s)
- Mohammad Momenian
- Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, CF705, Hung Hom, Kowloon, Hong Kong.
- Research Institute for Smart Ageing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong.
| | - Mahsa Vaghefi
- Department of Electrical Engineering, Shiraz Branch, Islamic Azad University, Shiraz, Iran
| | - Hamidreza Sadeghi
- Department of Computer Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Saeedeh Momtazi
- Department of Computer Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Lars Meyer
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, DE, Germany
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2
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Karimi H, Weber P, Zinn J. Information entropy facilitates (not impedes) lexical processing during language comprehension. Psychon Bull Rev 2024:10.3758/s13423-024-02463-x. [PMID: 38361106 DOI: 10.3758/s13423-024-02463-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/15/2024] [Indexed: 02/17/2024]
Abstract
It is well known that contextual predictability facilitates word identification, but it is less clear whether the uncertainty associated with the current context (i.e., its lexical entropy) influences sentence processing. On the one hand, high entropy contexts may lead to interference due to greater number of lexical competitors. On the other hand, predicting multiple lexical competitors may facilitate processing through the preactivation of shared semantic features. In this study, we examined whether entropy measured at the trial level (i.e., for each participant, for each item) corresponds to facilitatory or inhibitory effects. Trial-level entropy captures each individual's knowledge about specific contexts and is therefore a more valid and sensitive measure of entropy (relative to the commonly employed item-level entropy). Participants (N = 112) completed two experimental sessions (with counterbalanced orders) that were separated by a 3- to 14-day interval. In one session, they produced up to 10 completions for sentence fragments (N = 647). In another session, they read the same sentences including a target word (whose entropy value was calculated based on the produced completions) while reading times were measured. We observed a facilitatory (not inhibitory) effect of trial-level entropy on lexical processing over and above item-level measures of lexical predictability (including cloze probability, surprisal, and semantic constraint). Extra analyses revealed that greater semantic overlap between the target and the produced responses facilitated target processing. Thus, the results lend support to theories of lexical prediction maintaining that prediction involves broad activation of semantic features rather than activation of full lexical forms.
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Affiliation(s)
- Hossein Karimi
- Department of Psychology, Mississippi State University, 215 Magruder Hall, Mississippi State, MS, USA.
| | - Pete Weber
- Department of Psychology, Mississippi State University, 215 Magruder Hall, Mississippi State, MS, USA
| | - Jaden Zinn
- Department of Psychology, Mississippi State University, 215 Magruder Hall, Mississippi State, MS, USA
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3
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Li J, Hong B, Nolte G, Engel AK, Zhang D. EEG-based speaker-listener neural coupling reflects speech-selective attentional mechanisms beyond the speech stimulus. Cereb Cortex 2023; 33:11080-11091. [PMID: 37814353 DOI: 10.1093/cercor/bhad347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/01/2023] [Accepted: 09/04/2023] [Indexed: 10/11/2023] Open
Abstract
When we pay attention to someone, do we focus only on the sound they make, the word they use, or do we form a mental space shared with the speaker we want to pay attention to? Some would argue that the human language is no other than a simple signal, but others claim that human beings understand each other because they form a shared mental ground between the speaker and the listener. Our study aimed to explore the neural mechanisms of speech-selective attention by investigating the electroencephalogram-based neural coupling between the speaker and the listener in a cocktail party paradigm. The temporal response function method was employed to reveal how the listener was coupled to the speaker at the neural level. The results showed that the neural coupling between the listener and the attended speaker peaked 5 s before speech onset at the delta band over the left frontal region, and was correlated with speech comprehension performance. In contrast, the attentional processing of speech acoustics and semantics occurred primarily at a later stage after speech onset and was not significantly correlated with comprehension performance. These findings suggest a predictive mechanism to achieve speaker-listener neural coupling for successful speech comprehension.
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Affiliation(s)
- Jiawei Li
- Department of Psychology, School of Social Sciences, Tsinghua University, Beijing 100084, China
- Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China
- Department of Education and Psychology, Freie Universität Berlin, Habelschwerdter Allee, Berlin 14195, Germany
| | - Bo Hong
- Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China
- Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Guido Nolte
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg Eppendorf, Hamburg 20246, Germany
| | - Andreas K Engel
- Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg Eppendorf, Hamburg 20246, Germany
| | - Dan Zhang
- Department of Psychology, School of Social Sciences, Tsinghua University, Beijing 100084, China
- Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China
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4
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Ryskin R, Nieuwland MS. Prediction during language comprehension: what is next? Trends Cogn Sci 2023; 27:1032-1052. [PMID: 37704456 DOI: 10.1016/j.tics.2023.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 08/03/2023] [Accepted: 08/04/2023] [Indexed: 09/15/2023]
Abstract
Prediction is often regarded as an integral aspect of incremental language comprehension, but little is known about the cognitive architectures and mechanisms that support it. We review studies showing that listeners and readers use all manner of contextual information to generate multifaceted predictions about upcoming input. The nature of these predictions may vary between individuals owing to differences in language experience, among other factors. We then turn to unresolved questions which may guide the search for the underlying mechanisms. (i) Is prediction essential to language processing or an optional strategy? (ii) Are predictions generated from within the language system or by domain-general processes? (iii) What is the relationship between prediction and memory? (iv) Does prediction in comprehension require simulation via the production system? We discuss promising directions for making progress in answering these questions and for developing a mechanistic understanding of prediction in language.
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Affiliation(s)
- Rachel Ryskin
- Department of Cognitive and Information Sciences, University of California Merced, 5200 Lake Road, Merced, CA 95343, USA.
| | - Mante S Nieuwland
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands; Donders Institute for Brain, Cognition, and Behaviour, Nijmegen, The Netherlands
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5
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Kumar M, Goldstein A, Michelmann S, Zacks JM, Hasson U, Norman KA. Bayesian Surprise Predicts Human Event Segmentation in Story Listening. Cogn Sci 2023; 47:e13343. [PMID: 37867379 DOI: 10.1111/cogs.13343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 08/28/2023] [Accepted: 09/01/2023] [Indexed: 10/24/2023]
Abstract
Event segmentation theory posits that people segment continuous experience into discrete events and that event boundaries occur when there are large transient increases in prediction error. Here, we set out to test this theory in the context of story listening, by using a deep learning language model (GPT-2) to compute the predicted probability distribution of the next word, at each point in the story. For three stories, we used the probability distributions generated by GPT-2 to compute the time series of prediction error. We also asked participants to listen to these stories while marking event boundaries. We used regression models to relate the GPT-2 measures to the human segmentation data. We found that event boundaries are associated with transient increases in Bayesian surprise but not with a simpler measure of prediction error (surprisal) that tracks, for each word in the story, how strongly that word was predicted at the previous time point. These results support the hypothesis that prediction error serves as a control mechanism governing event segmentation and point to important differences between operational definitions of prediction error.
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Affiliation(s)
- Manoj Kumar
- Princeton Neuroscience Institute, Princeton University
| | - Ariel Goldstein
- Department of Cognitive and Brain Sciences and Business School, Hebrew University
- Google Research, Tel-Aviv
| | | | - Jeffrey M Zacks
- Department of Psychological & Brain Sciences, Washington University in St. Louis
| | - Uri Hasson
- Princeton Neuroscience Institute, Princeton University
- Department of Psychology, Princeton University
| | - Kenneth A Norman
- Princeton Neuroscience Institute, Princeton University
- Department of Psychology, Princeton University
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6
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Slaats S, Weissbart H, Schoffelen JM, Meyer AS, Martin AE. Delta-Band Neural Responses to Individual Words Are Modulated by Sentence Processing. J Neurosci 2023; 43:4867-4883. [PMID: 37221093 PMCID: PMC10312058 DOI: 10.1523/jneurosci.0964-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 04/17/2023] [Accepted: 04/27/2023] [Indexed: 05/25/2023] Open
Abstract
To understand language, we need to recognize words and combine them into phrases and sentences. During this process, responses to the words themselves are changed. In a step toward understanding how the brain builds sentence structure, the present study concerns the neural readout of this adaptation. We ask whether low-frequency neural readouts associated with words change as a function of being in a sentence. To this end, we analyzed an MEG dataset by Schoffelen et al. (2019) of 102 human participants (51 women) listening to sentences and word lists, the latter lacking any syntactic structure and combinatorial meaning. Using temporal response functions and a cumulative model-fitting approach, we disentangled delta- and theta-band responses to lexical information (word frequency), from responses to sensory and distributional variables. The results suggest that delta-band responses to words are affected by sentence context in time and space, over and above entropy and surprisal. In both conditions, the word frequency response spanned left temporal and posterior frontal areas; however, the response appeared later in word lists than in sentences. In addition, sentence context determined whether inferior frontal areas were responsive to lexical information. In the theta band, the amplitude was larger in the word list condition ∼100 milliseconds in right frontal areas. We conclude that low-frequency responses to words are changed by sentential context. The results of this study show how the neural representation of words is affected by structural context and as such provide insight into how the brain instantiates compositionality in language.SIGNIFICANCE STATEMENT Human language is unprecedented in its combinatorial capacity: we are capable of producing and understanding sentences we have never heard before. Although the mechanisms underlying this capacity have been described in formal linguistics and cognitive science, how they are implemented in the brain remains to a large extent unknown. A large body of earlier work from the cognitive neuroscientific literature implies a role for delta-band neural activity in the representation of linguistic structure and meaning. In this work, we combine these insights and techniques with findings from psycholinguistics to show that meaning is more than the sum of its parts; the delta-band MEG signal differentially reflects lexical information inside and outside sentence structures.
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Affiliation(s)
- Sophie Slaats
- Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, The Netherlands
- The International Max Planck Research School for Language Sciences, 6525 XD Nijmegen, The Netherlands
| | - Hugo Weissbart
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN Nijmegen, The Netherlands
| | - Jan-Mathijs Schoffelen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN Nijmegen, The Netherlands
| | - Antje S Meyer
- Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN Nijmegen, The Netherlands
| | - Andrea E Martin
- Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 EN Nijmegen, The Netherlands
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7
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Pérez A, Davis MH. Speaking and listening to inter-brain relationships. Cortex 2023; 159:54-63. [PMID: 36608420 DOI: 10.1016/j.cortex.2022.12.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/11/2022] [Accepted: 12/06/2022] [Indexed: 12/23/2022]
Abstract
Studies of inter-brain relationships thrive, and yet many reservations regarding their scope and interpretation of these phenomena have been raised by the scientific community. It is thus essential to establish common ground on methodological and conceptual definitions related to this topic and to open debate about any remaining points of uncertainty. We here offer insights to improve the conceptual clarity and empirical standards offered by social neuroscience studies of inter-personal interaction using hyperscanning with a particular focus on verbal communication.
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Affiliation(s)
- Alejandro Pérez
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK.
| | - Matthew H Davis
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK
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8
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Gastaldon S, Busan P, Arcara G, Peressotti F. Inefficient speech-motor control affects predictive speech comprehension: atypical electrophysiological correlates in stuttering. Cereb Cortex 2023:6995383. [PMID: 36682885 DOI: 10.1093/cercor/bhad004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 12/29/2022] [Accepted: 12/30/2022] [Indexed: 01/24/2023] Open
Abstract
Listeners predict upcoming information during language comprehension. However, how this ability is implemented is still largely unknown. Here, we tested the hypothesis proposing that language production mechanisms have a role in prediction. We studied 2 electroencephalographic correlates of predictability during speech comprehension-pre-target alpha-beta (8-30 Hz) power decrease and the post-target N400 event-related potential effect-in a population with impaired speech-motor control, i.e. adults who stutter (AWS), compared to typically fluent adults (TFA). Participants listened to sentences that could either constrain towards a target word or not, modulating its predictability. As a complementary task, participants also performed context-driven word production. Compared to TFA, AWS not only displayed atypical neural responses in production, but, critically, they showed a different pattern also in comprehension. Specifically, while TFA showed the expected pre-target power decrease, AWS showed a power increase in frontal regions, associated with speech-motor control. In addition, the post-target N400 effect was reduced for AWS with respect to TFA. Finally, we found that production and comprehension power changes were positively correlated in TFA, but not in AWS. Overall, the results support the idea that processes and neural structures prominently devoted to speech planning also support prediction during speech comprehension.
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Affiliation(s)
- Simone Gastaldon
- Dipartimento di Psicologia dello Sviluppo e della Socializzazione (DPSS), University of Padova, Via Venezia 8, Padova (PD) 35131, Italy.,Padova Neuroscience Center (PNC), University of Padova, Via Giuseppe Orus 2/B, Padova (PD) 35131, Italy
| | - Pierpaolo Busan
- IRCCS Ospedale San Camillo, Via Alberoni 70, Lido (VE) 30126, Italy
| | - Giorgio Arcara
- IRCCS Ospedale San Camillo, Via Alberoni 70, Lido (VE) 30126, Italy
| | - Francesca Peressotti
- Dipartimento di Psicologia dello Sviluppo e della Socializzazione (DPSS), University of Padova, Via Venezia 8, Padova (PD) 35131, Italy.,Padova Neuroscience Center (PNC), University of Padova, Via Giuseppe Orus 2/B, Padova (PD) 35131, Italy.,Centro Interdipartimentale di Ricerca "I-APPROVE-International Auditory Processing Project in Venice", University of Padova, Via Belzoni 160, Padova (PD) 35121, Italy
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9
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Zhong S, Chen N, Lai S, Shan Y, Li Z, Chen J, Luo A, Zhang Y, Lv S, He J, Wang Y, Yao Z, Jia Y. Association between cognitive impairments and aberrant dynamism of overlapping brain sub-networks in unmedicated major depressive disorder: A resting-state MEG study. J Affect Disord 2023; 320:576-589. [PMID: 36179776 DOI: 10.1016/j.jad.2022.09.069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 08/24/2022] [Accepted: 09/20/2022] [Indexed: 02/02/2023]
Abstract
OBJECTIVE Little is known about the pathogenesis underlying cognitive impairment in major depressive disorder (MDD). We aimed to explore the mechanisms of cognitive impairments among patients with MDD by investigating the dynamics of overlapping brain sub-networks. METHODS Forty unmedicated patients with MDD and 28 healthy controls (HC) were enrolled in this study. Cognitive function was measured using the Chinese versions of MATRICS Consensus Cognitive Battery (MCCB). All participants were scanned using a whole-head resting-state magnetoencephalography (MEG) machine. The dynamism of neural sub-networks was analyzed based on the detection of overlapping communities in five frequency bands of oscillatory brain signals. RESULTS MDD demonstrated poorer cognitive performance in six domains compared to HC. The difference in community detection (functional integration mode) in MDD was frequency-dependent. MDD showed significantly decreased community dynamics in all frequency bands compared to HC. Specifically, differences in the visual network (VN) and default mode network (DMN) were detected in all frequency bands, differences in the cognitive control network (CCN) were detected in the alpha2 and beta frequency bands, and differences in the bilateral limbic network (BLN) were only detected in the beta frequency band. Moreover, community dynamics in the alpha2 frequency band were positively correlated with verbal learning and reasoning problem solving abilities in MDD. CONCLUSIONS Our study found that decreasing in the dynamics of overlapping sub-networks may differ by frequency bands. The aberrant dynamics of overlapping neural sub-networks revealed by frequency-specific MEG signals may provide new information on the mechanism of cognitive impairments that result from MDD.
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Affiliation(s)
- Shuming Zhong
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Nan Chen
- School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
| | - Shunkai Lai
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Yanyan Shan
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Zhinan Li
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Junhao Chen
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Aiming Luo
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Yiliang Zhang
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Sihui Lv
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Jiali He
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China
| | - Ying Wang
- Medical Imaging Center, First Affiliated Hospital, Jinan University, Guangzhou 510630, China.
| | - Zhijun Yao
- School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China.
| | - Yanbin Jia
- Department of Psychiatry, First Affiliated Hospital, Jinan University, Guangzhou 510630, China.
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10
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Momsen J, Schneider JM, Abel AD. Developmental differences in EEG oscillations supporting the identification of novel word meaning from context. Dev Cogn Neurosci 2022; 58:101185. [PMID: 36521344 PMCID: PMC9768236 DOI: 10.1016/j.dcn.2022.101185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 11/16/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022] Open
Abstract
Implicit learning about new words by picking up on associative information in the contexts they appear in is an important aspect of vocabulary growth. The current study investigated the neural correlates that underlie how school-aged children and adolescents identify the meaning of novel words embedded within sentence contexts. Importantly, we examine how differences in the brain response to novel words and their context differ as a function of 1) explicit learning success, i.e., whether novel word meanings can be correctly estimated in isolation after a learning opportunity, and 2) individual differences in offline language aptitude as well as age across our cohort (N = 82; 8-16 years). Using a regression-based analysis, we identified the unique influence of these individuals difference metrics by using both measures within the same series of models. The most notable finding from our analysis was a frequency-specific dissociation between the way age and language abilities held relationships with task-relevant oscillatory activity during the novel word meaning task: language abilities associated with task-relevant changes in beta band activity during sentence processing, while age associated with task-relevant changes in theta band activity during pseudoword processing. These effects reflect the how the neural correlates of mapping semantic meaning from sentence contexts-an important skill for word learning-is uniquely influenced by the maturity of language abilities as well as age.
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Affiliation(s)
- Jacob Momsen
- Joint Doctoral Program in Language and Communicative Disorders, San Diego State University and UC San Diego, United States
| | - Julie M. Schneider
- Louisiana State University, United States,The University of Delaware, United States
| | - Alyson D. Abel
- San Diego State University, United States,Correspondence to: San Diego State University, 5500 Campanile Dr., San Diego, CA 92182, United States.
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11
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Youssofzadeh V, Conant L, Stout J, Ustine C, Humphries C, Gross WL, Shah-Basak P, Mathis J, Awe E, Allen L, DeYoe EA, Carlson C, Anderson CT, Maganti R, Hermann B, Nair VA, Prabhakaran V, Meyerand B, Binder JR, Raghavan M. Late dominance of the right hemisphere during narrative comprehension. Neuroimage 2022; 264:119749. [PMID: 36379420 PMCID: PMC9772156 DOI: 10.1016/j.neuroimage.2022.119749] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 10/12/2022] [Accepted: 11/11/2022] [Indexed: 11/15/2022] Open
Abstract
PET and fMRI studies suggest that auditory narrative comprehension is supported by a bilateral multilobar cortical network. The superior temporal resolution of magnetoencephalography (MEG) makes it an attractive tool to investigate the dynamics of how different neuroanatomic substrates engage during narrative comprehension. Using beta-band power changes as a marker of cortical engagement, we studied MEG responses during an auditory story comprehension task in 31 healthy adults. The protocol consisted of two runs, each interleaving 7 blocks of the story comprehension task with 15 blocks of an auditorily presented math task as a control for phonological processing, working memory, and attention processes. Sources at the cortical surface were estimated with a frequency-resolved beamformer. Beta-band power was estimated in the frequency range of 16-24 Hz over 1-sec epochs starting from 400 msec after stimulus onset until the end of a story or math problem presentation. These power estimates were compared to 1-second epochs of data before the stimulus block onset. The task-related cortical engagement was inferred from beta-band power decrements. Group-level source activations were statistically compared using non-parametric permutation testing. A story-math contrast of beta-band power changes showed greater bilateral cortical engagement within the fusiform gyrus, inferior and middle temporal gyri, parahippocampal gyrus, and left inferior frontal gyrus (IFG) during story comprehension. A math-story contrast of beta power decrements showed greater bilateral but left-lateralized engagement of the middle frontal gyrus and superior parietal lobule. The evolution of cortical engagement during five temporal windows across the presentation of stories showed significant involvement during the first interval of the narrative of bilateral opercular and insular regions as well as the ventral and lateral temporal cortex, extending more posteriorly on the left and medially on the right. Over time, there continued to be sustained right anterior ventral temporal engagement, with increasing involvement of the right anterior parahippocampal gyrus, STG, MTG, posterior superior temporal sulcus, inferior parietal lobule, frontal operculum, and insula, while left hemisphere engagement decreased. Our findings are consistent with prior imaging studies of narrative comprehension, but in addition, they demonstrate increasing right-lateralized engagement over the course of narratives, suggesting an important role for these right-hemispheric regions in semantic integration as well as social and pragmatic inference processing.
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Affiliation(s)
- Vahab Youssofzadeh
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA,Corresponding author. (V. Youssofzadeh)
| | - Lisa Conant
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Jeffrey Stout
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Candida Ustine
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | | | - William L. Gross
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA,Anesthesiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | | | - Jed Mathis
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA,Radiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Elizabeth Awe
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Linda Allen
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Edgar A. DeYoe
- Radiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Chad Carlson
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | | | - Rama Maganti
- Neurology, University of Wisconsin-Madison, Madison, WI, USA
| | - Bruce Hermann
- Neurology, University of Wisconsin-Madison, Madison, WI, USA
| | - Veena A. Nair
- Radiology, University of Wisconsin-Madison, Madison, WI, USA
| | - Vivek Prabhakaran
- Radiology, University of Wisconsin-Madison, Madison, WI, USA,Medical Physics, University of Wisconsin-Madison, Madison, WI, USA,Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Beth Meyerand
- Radiology, University of Wisconsin-Madison, Madison, WI, USA,Medical Physics, University of Wisconsin-Madison, Madison, WI, USA,Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Manoj Raghavan
- Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
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12
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Abstract
Understanding spoken language requires transforming ambiguous acoustic streams into a hierarchy of representations, from phonemes to meaning. It has been suggested that the brain uses prediction to guide the interpretation of incoming input. However, the role of prediction in language processing remains disputed, with disagreement about both the ubiquity and representational nature of predictions. Here, we address both issues by analyzing brain recordings of participants listening to audiobooks, and using a deep neural network (GPT-2) to precisely quantify contextual predictions. First, we establish that brain responses to words are modulated by ubiquitous predictions. Next, we disentangle model-based predictions into distinct dimensions, revealing dissociable neural signatures of predictions about syntactic category (parts of speech), phonemes, and semantics. Finally, we show that high-level (word) predictions inform low-level (phoneme) predictions, supporting hierarchical predictive processing. Together, these results underscore the ubiquity of prediction in language processing, showing that the brain spontaneously predicts upcoming language at multiple levels of abstraction.
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Heilbron M, Armeni K, Schoffelen JM, Hagoort P, de Lange FP. A hierarchy of linguistic predictions during natural language comprehension. Proc Natl Acad Sci U S A 2022; 119:e2201968119. [PMID: 35921434 DOI: 10.1101/2020.12.03.410399] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/21/2023] Open
Abstract
Understanding spoken language requires transforming ambiguous acoustic streams into a hierarchy of representations, from phonemes to meaning. It has been suggested that the brain uses prediction to guide the interpretation of incoming input. However, the role of prediction in language processing remains disputed, with disagreement about both the ubiquity and representational nature of predictions. Here, we address both issues by analyzing brain recordings of participants listening to audiobooks, and using a deep neural network (GPT-2) to precisely quantify contextual predictions. First, we establish that brain responses to words are modulated by ubiquitous predictions. Next, we disentangle model-based predictions into distinct dimensions, revealing dissociable neural signatures of predictions about syntactic category (parts of speech), phonemes, and semantics. Finally, we show that high-level (word) predictions inform low-level (phoneme) predictions, supporting hierarchical predictive processing. Together, these results underscore the ubiquity of prediction in language processing, showing that the brain spontaneously predicts upcoming language at multiple levels of abstraction.
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Affiliation(s)
- Micha Heilbron
- Donders Institute, Radboud University, 6525 EN Nijmegen, The Netherlands
- Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, The Netherlands
| | - Kristijan Armeni
- Donders Institute, Radboud University, 6525 EN Nijmegen, The Netherlands
| | | | - Peter Hagoort
- Donders Institute, Radboud University, 6525 EN Nijmegen, The Netherlands
- Max Planck Institute for Psycholinguistics, 6525 XD Nijmegen, The Netherlands
| | - Floris P de Lange
- Donders Institute, Radboud University, 6525 EN Nijmegen, The Netherlands
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14
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Armeni K, Güçlü U, van Gerven M, Schoffelen JM. A 10-hour within-participant magnetoencephalography narrative dataset to test models of language comprehension. Sci Data 2022; 9:278. [PMID: 35676293 PMCID: PMC9177538 DOI: 10.1038/s41597-022-01382-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 05/10/2022] [Indexed: 11/13/2022] Open
Abstract
Recently, cognitive neuroscientists have increasingly studied the brain responses to narratives. At the same time, we are witnessing exciting developments in natural language processing where large-scale neural network models can be used to instantiate cognitive hypotheses in narrative processing. Yet, they learn from text alone and we lack ways of incorporating biological constraints during training. To mitigate this gap, we provide a narrative comprehension magnetoencephalography (MEG) data resource that can be used to train neural network models directly on brain data. We recorded from 3 participants, 10 separate recording hour-long sessions each, while they listened to audiobooks in English. After story listening, participants answered short questions about their experience. To minimize head movement, the participants wore MEG-compatible head casts, which immobilized their head position during recording. We report a basic evoked-response analysis showing that the responses accurately localize to primary auditory areas. The responses are robust and conserved across 10 sessions for every participant. We also provide usage notes and briefly outline possible future uses of the resource.
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Affiliation(s)
- Kristijan Armeni
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Umut Güçlü
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Marcel van Gerven
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Jan-Mathijs Schoffelen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
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15
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Huizeling E, Arana S, Hagoort P, Schoffelen JM. Lexical Frequency and Sentence Context Influence the Brain's Response to Single Words. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2022; 3:149-179. [PMID: 37215333 PMCID: PMC10158670 DOI: 10.1162/nol_a_00054] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 09/03/2021] [Indexed: 05/24/2023]
Abstract
Typical adults read remarkably quickly. Such fast reading is facilitated by brain processes that are sensitive to both word frequency and contextual constraints. It is debated as to whether these attributes have additive or interactive effects on language processing in the brain. We investigated this issue by analysing existing magnetoencephalography data from 99 participants reading intact and scrambled sentences. Using a cross-validated model comparison scheme, we found that lexical frequency predicted the word-by-word elicited MEG signal in a widespread cortical network, irrespective of sentential context. In contrast, index (ordinal word position) was more strongly encoded in sentence words, in left front-temporal areas. This confirms that frequency influences word processing independently of predictability, and that contextual constraints affect word-by-word brain responses. With a conservative multiple comparisons correction, only the interaction between lexical frequency and surprisal survived, in anterior temporal and frontal cortex, and not between lexical frequency and entropy, nor between lexical frequency and index. However, interestingly, the uncorrected index × frequency interaction revealed an effect in left frontal and temporal cortex that reversed in time and space for intact compared to scrambled sentences. Finally, we provide evidence to suggest that, in sentences, lexical frequency and predictability may independently influence early (<150 ms) and late stages of word processing, but also interact during late stages of word processing (>150-250 ms), thus helping to converge previous contradictory eye-tracking and electrophysiological literature. Current neurocognitive models of reading would benefit from accounting for these differing effects of lexical frequency and predictability on different stages of word processing.
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Affiliation(s)
- Eleanor Huizeling
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Sophie Arana
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Peter Hagoort
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
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16
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Zheng Y, Zhao Z, Yang X, Li X. The impact of musical expertise on anticipatory semantic processing during online speech comprehension: An electroencephalography study. BRAIN AND LANGUAGE 2021; 221:105006. [PMID: 34392023 DOI: 10.1016/j.bandl.2021.105006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 07/29/2021] [Accepted: 07/30/2021] [Indexed: 06/13/2023]
Abstract
Musical experience has been found to aid speech perception. This electroencephalography study further examined whether and how musical expertise affects high-level predictive semantic processing in speech comprehension. Musicians and non-musicians listened to semantically strongly/weakly constraining sentences, with each sentence being primed by a congruent/incongruent sentence-prosody. At the target nouns, a N400 reduction effect (strongly vs. weakly constraining) was observed in both groups, with the onset-latency of this effect being delayed for incongruent (vs. congruent) priming. At the transitive verbs preceding these target nouns, musicians' event-related-potential amplitude (in incongruent-priming) and beta-band oscillatory power (in congruent- and incongruent-priming) showed a semantic-constraint effect, and were correlated with the predictability of incoming nouns; non-musicians only demonstrated an event-related-potential semantic-constraint effect, which was correlated with the predictability of current verbs. These results indicate musical expertise enhances semantic prediction tendency in speech comprehension, and this effect might be not just an aftereffect of facilitated acoustic/phonological processing.
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Affiliation(s)
- Yuanyi Zheng
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100149, China
| | - Zitong Zhao
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100149, China
| | - Xiaohong Yang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100149, China
| | - Xiaoqing Li
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100149, China.
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Youssofzadeh V, Stout J, Ustine C, Gross WL, Conant LL, Humphries CJ, Binder JR, Raghavan M. Mapping language from MEG beta power modulations during auditory and visual naming. Neuroimage 2020; 220:117090. [DOI: 10.1016/j.neuroimage.2020.117090] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 06/06/2020] [Accepted: 06/23/2020] [Indexed: 01/22/2023] Open
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18
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Koskinen M, Kurimo M, Gross J, Hyvärinen A, Hari R. Brain activity reflects the predictability of word sequences in listened continuous speech. Neuroimage 2020; 219:116936. [PMID: 32474080 DOI: 10.1016/j.neuroimage.2020.116936] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 04/24/2020] [Accepted: 05/07/2020] [Indexed: 11/17/2022] Open
Abstract
Natural speech builds on contextual relations that can prompt predictions of upcoming utterances. To study the neural underpinnings of such predictive processing we asked 10 healthy adults to listen to a 1-h-long audiobook while their magnetoencephalographic (MEG) brain activity was recorded. We correlated the MEG signals with acoustic speech envelope, as well as with estimates of Bayesian word probability with and without the contextual word sequence (N-gram and Unigram, respectively), with a focus on time-lags. The MEG signals of auditory and sensorimotor cortices were strongly coupled to the speech envelope at the rates of syllables (4-8 Hz) and of prosody and intonation (0.5-2 Hz). The probability structure of word sequences, independently of the acoustical features, affected the ≤ 2-Hz signals extensively in auditory and rolandic regions, in precuneus, occipital cortices, and lateral and medial frontal regions. Fine-grained temporal progression patterns occurred across brain regions 100-1000 ms after word onsets. Although the acoustic effects were observed in both hemispheres, the contextual influences were statistically significantly lateralized to the left hemisphere. These results serve as a brain signature of the predictability of word sequences in listened continuous speech, confirming and extending previous results to demonstrate that deeply-learned knowledge and recent contextual information are employed dynamically and in a left-hemisphere-dominant manner in predicting the forthcoming words in natural speech.
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Affiliation(s)
- Miika Koskinen
- Medicum, Faculty of Medicine, P.O. Box 63, FI-00014, University of Helsinki, Finland; Department of Neuroscience and Biomedical Engineering, P.O. Box 12200, FI-00076, Aalto University, Finland; Institute of Neuroscience and Psychology, University of Glasgow, 58 Hillhead Street, Glasgow, G12 8QB, UK; MEG Core, Aalto NeuroImaging, FI-00076, Aalto University, Finland.
| | - Mikko Kurimo
- Department of Signal Processing and Acoustics, P.O. Box 13000, FI-00076, Aalto University, Finland
| | - Joachim Gross
- Institute of Neuroscience and Psychology, University of Glasgow, 58 Hillhead Street, Glasgow, G12 8QB, UK; Institute for Biomagnetism and Biosignalanalysis, University of Muenster, 48149, Muenster, Germany
| | - Aapo Hyvärinen
- Department of Computer Science, P.O. Box 68, FI-00014, University of Helsinki, Finland
| | - Riitta Hari
- Department of Neuroscience and Biomedical Engineering, P.O. Box 12200, FI-00076, Aalto University, Finland; Department of Art, P.O. Box 31000, FI-00076, Aalto University, Finland
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19
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Liu Z, Shu S, Lu L, Ge J, Gao JH. Spatiotemporal dynamics of predictive brain mechanisms during speech processing: an MEG study. BRAIN AND LANGUAGE 2020; 203:104755. [PMID: 32007671 DOI: 10.1016/j.bandl.2020.104755] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 12/09/2019] [Accepted: 01/15/2020] [Indexed: 06/10/2023]
Abstract
Rapid and efficient speech processing benefits from the prediction derived from prior expectations based on the identification of individual words. It is known that speech processing is carried out within a distributed frontotemporal network. However, the spatiotemporal causal dynamics of predictive brain mechanisms in sound-to-meaning mapping within this network remain unclear. Using magnetoencephalography, we adopted a semantic anomaly paradigm which consists of expected, unexpected and time-reversed Mandarin Chinese speech, and localized the effects of violated expectation in frontotemporal brain regions, the sensorimotor cortex and the supramarginal gyrus from 250 ms relative to the target words. By further investigating the causal cortical dynamics, we provided the description of the causal dynamic network within the framework of the dual stream model, and highlighted the importance of the connections within the ventral pathway, the top-down modulation from the left inferior frontal gyrus and the cross-stream integration during the speech processing of violated expectation.
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Affiliation(s)
- Zhaowei Liu
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Su Shu
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Lingxi Lu
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Jianqiao Ge
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China.
| | - Jia-Hong Gao
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China.
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20
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Evaluating information-theoretic measures of word prediction in naturalistic sentence reading. Neuropsychologia 2019; 134:107198. [DOI: 10.1016/j.neuropsychologia.2019.107198] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 08/09/2019] [Accepted: 09/19/2019] [Indexed: 11/18/2022]
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