Linguistic Structure and Meaning Organize Neural Oscillations into a Content-Specific Hierarchy

Kaufeld, Greta; Bosker, Hans R.; Oever, Sanne ten; Alday, Phillip M.; Meyer, Antje S.; Martin, Andrea E.

doi:10.1523/jneurosci.0302-20.2020

Cited by 107 publications

(184 citation statements)

References 63 publications

(81 reference statements)

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“…This could further support the speculation that the two LPTL effects underlyingly reflect different processes, only one of which (bottom-up structure building) appears in β -band activity. Cross-frequency β-θ coupling is specifically suggested to support syntactic predictions 48 , 52 , while other sets of results have shown a modulation of the δ -band spectral components by combinatorial variables 53 . More research is needed to address the different models directly, and to further bridge ROI results and spectral analyses.…”

Section: Discussionmentioning

confidence: 85%

Left posterior temporal cortex is sensitive to syntax within conceptually matched Arabic expressions

Matar

Dirani

Marantz

et al. 2021

Sci Rep

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During language comprehension, the brain processes not only word meanings, but also the grammatical structure—the “syntax”—that strings words into phrases and sentences. Yet the neural basis of syntax remains contentious, partly due to the elusiveness of experimental designs that vary structure independently of meaning-related variables. Here, we exploit Arabic’s grammatical properties, which enable such a design. We collected magnetoencephalography (MEG) data while participants read the same noun-adjective expressions with zero, one, or two contiguously-written definite articles (e.g., ‘chair purple’; ‘the-chair purple’; ‘the-chair the-purple’), representing equivalent concepts, but with different levels of syntactic complexity (respectively, indefinite phrases: ‘a purple chair’; sentences: ‘The chair is purple.’; definite phrases: ‘the purple chair’). We expected regions processing syntax to respond differently to simple versus complex structures. Single-word controls (‘chair’/‘purple’) addressed definiteness-based accounts. In noun-adjective expressions, syntactic complexity only modulated activity in the left posterior temporal lobe (LPTL), ~ 300 ms after each word’s onset: indefinite phrases induced more MEG-measured positive activity. The effects disappeared in single-word tokens, ruling out non-syntactic interpretations. In contrast, left anterior temporal lobe (LATL) activation was driven by meaning. Overall, the results support models implicating the LPTL in structure building and the LATL in early stages of conceptual combination.

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Section: Discussionmentioning

confidence: 85%

Left posterior temporal cortex is sensitive to syntax within conceptually matched Arabic expressions

Matar

Dirani

Marantz

et al. 2021

Sci Rep

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“…Extending the frequency band of EEG for the model can be considered as a possible way to improve the detection accuracy. Recently, many studies have argued that neural signals below 2 Hz may reflect representation of prosodic information or larger linguistics unit such as phrases [ 38 , 39 , 40 ]. This information could be beneficial for the model to identify a participant′s auditory attention because it would give additional clues to their state, in terms of speech processing.…”

Section: Discussionmentioning

confidence: 99%

Implementation of an Online Auditory Attention Detection Model with Electroencephalography in a Dichotomous Listening Experiment

Baek

Chung

Lim

2021

Sensors

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Auditory attention detection (AAD) is the tracking of a sound source to which a listener is attending based on neural signals. Despite expectation for the applicability of AAD in real-life, most AAD research has been conducted on recorded electroencephalograms (EEGs), which is far from online implementation. In the present study, we attempted to propose an online AAD model and to implement it on a streaming EEG. The proposed model was devised by introducing a sliding window into the linear decoder model and was simulated using two datasets obtained from separate experiments to evaluate the feasibility. After simulation, the online model was constructed and evaluated based on the streaming EEG of an individual, acquired during a dichotomous listening experiment. Our model was able to detect the transient direction of a participant’s attention on the order of one second during the experiment and showed up to 70% average detection accuracy. We expect that the proposed online model could be applied to develop adaptive hearing aids or neurofeedback training for auditory attention and speech perception.

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“…While the study of the electrophysiology of sentence comprehension has largely focussed on ERPs (for overviews, see , 2019Osterhout & Holcomb, 1995), recent evidence demonstrates that sentence processing is associated with dynamic activity in different frequency bands (e.g., Bastiaansen et al, 2002;Kaufeld et al, 2020;Kepinska, Pereda, Caspers, & Schiller, 2017;Lam, Schoffelen, Udden, Hulten, & Hagoort, 2016;Roehm et al, 2001;. For example, linear beta power (~ 13 -30 Hz) increases have been observed during the presentation of grammatical sentences (Bastiaansen & Hagoort, 2015;Lam et al, 2016;Wang et al, 2012), argued to reflect the propagation of top-down predictions during sentence comprehension (Lam, et al, 2016;Wang et al, 2012).…”

Section: Neural Oscillations As Windows Onto the Sleep-based Consolidmentioning

confidence: 99%

Slow oscillation-spindle coupling predicts sequence-based language learning

Cross

Helfrich

Corcoran

et al. 2020

Preprint

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word count: 174 Introduction word count: 1,756 Discussion word count: 2,677ABSTRACT Language is one of the most defining human capabilities, involving the coordination of brain networks that generalise the meaning of linguistic units of varying complexity. On a neural level, neocortical slow waves and thalamic spindles during sleep facilitate the reactivation of newly encoded memory traces, manifesting in distinct oscillatory activity during retrieval. However, it is currently unknown if the effect of sleep on memory extends to the generalisation of the mechanisms that subserve sentence comprehension. We address this question by analysing electroencephalogram data recorded from 36 participants during an artificial language learning task and an 8hr nocturnal sleep period. We found that a period of sleep was associated with increased alpha/beta synchronisation and improved behavioural performance. Cross-frequency coupling analyses also revealed that spindle-slow wave coupling predicted the consolidation of varying word order permutations, which was associated with distinct patterns of task-related oscillatory activity during sentence processing. Taken together, this study presents converging behavioural and neurophysiological evidence for a role of sleep in the consolidation of higher order language learning and associated oscillatory neuronal activity.Keywords: Sleep and memory; language learning; modified miniature language; sentence processing; neuronal oscillations SIGNIFICANCE STATEMENTThe endogenous temporal coordination of neural oscillations supports information processing during both wake and sleep states. Here we demonstrate that spindle-slow wave coupling during non-rapid eye movement sleep predicts the consolidation of complex grammatical rules and modulates task-related oscillatory dynamics previously implicated in sentence processing. We show that increases in alpha/beta synchronisation predict enhanced sensitivity to grammatical violations after a period of sleep and strong spindle-slow wave coupling modulates subsequent task-related theta activity to influence behaviour. Our findings reveal a complex interaction between both wake-and sleep-related oscillatory dynamics during the early stages of language learning beyond the single word level.

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Linguistic Structure and Meaning Organize Neural Oscillations into a Content-Specific Hierarchy

Abstract: Group "Language and Computation in Neural Systems" and by the Netherlands Organization for Scientific Research (grant 016.Vidi.188.029).

Cited by 107 publications

References 63 publications

Left posterior temporal cortex is sensitive to syntax within conceptually matched Arabic expressions

Left posterior temporal cortex is sensitive to syntax within conceptually matched Arabic expressions

Implementation of an Online Auditory Attention Detection Model with Electroencephalography in a Dichotomous Listening Experiment

Slow oscillation-spindle coupling predicts sequence-based language learning

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