Robust neuronal oscillatory entrainment to speech displays individual variation in lateralisation

Lam, Nietzsche H. L.; Hultén, Annika; Hagoort, Peter; Schoffelen, Jan Mathijs

doi:10.1080/23273798.2018.1437456

Cited by 12 publications

(8 citation statements)

References 44 publications

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“…This 237 revealed a clear peak around auditory cortex ( Fig S7) 238 especially in the right hemisphere. This aligns with 239 prior work [40,41] and confirms that this approach 240 can localise which areas are especially sensitive to 241 a given regressor. We then tested the three pre- negative deflection was already explained by the overall lexical surprise, which was included as a nuisance regressor ( Figure S10).…”

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confidence: 73%

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A hierarchy of linguistic predictions during natural language comprehension

Heilbron

Armeni

Schoffelen

et al. 2020

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Understanding spoken language requires transforming ambiguous stimulus streams into a hierarchy of increasingly abstract representations, ranging from speech sounds to meaning. It has been suggested that the brain uses predictive computations to guide the interpretation of incoming information. However, the exact role of prediction in language understanding remains unclear, with widespread disagreement about both the ubiquity of prediction, and the level of representation at which predictions unfold. Here, we address both issues by analysing brain recordings of participants listening to audiobooks, and using a state-of-the-art deep neural network (GPT-2) to quantify predictions in a fine-grained, contextual fashion. First, we establish clear evidence for predictive processing, confirming that brain responses to words are modulated by probabilistic predictions. Next, we factorised the model-based predictions into distinct linguistic dimensions, revealing dissociable neural signatures of syntactic, phonemic and semantic predictions. Finally, we show that high-level (word) predictions inform low-level (phoneme) predictions, supporting theories of hierarchical predictive processing. Together, these results underscore the ubiquity of prediction in language processing, and demonstrate that linguistic prediction is not implemented by a single system but occurs throughout the language network, forming a hierarchy of linguistic predictions across all levels of analysis.

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confidence: 73%

“…LANGUAGE NETWORK DEFINITION The language network was defined as temporal cortex plus temporo-parietal junction, and IFG and dorsolateral prefrontal cortex; all bilaterally. In terms of Brodmann areas this corresponded to 20, 21, 22,38,39,40,41,42,44,45, 46 and 47, amounting to a total of 100 out of 370 cortical parcels.…”

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confidence: 99%

A hierarchy of linguistic predictions during natural language comprehension

Heilbron

Armeni

Schoffelen

et al. 2020

Preprint

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“…power, phase) in the Magnetoencephalography/Electroencephalography (M/EEG) data concurrently recorded (e.g. Ahissar et al, 2001;Gross et al, 2013;Keitel, Gross, & Kayser, 2018;Lam, Hultén, Hagoort, & Schoffelen, 2018). Others have instead measured M/EEG while people listen to speech with known spectral characteristics centred at specific rates of interest (e.g.…”

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confidence: 99%

Balancing exogenous and endogenous cortical rhythms for speech and language requires a lot of entraining: a commentary on Meyer, Sun & Martin (2020)

Lewis

2020

Language, Cognition and Neuroscience

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“…Using magnetoencephalography (MEG) signals from 200 subjects, 55 we performed a quantitative assessment of the sensory modality independent brain 56 activity following word onset during sentence processing. The MEG data forms part 57 of a large publicly available dataset [40], and has been used in other publications as 58 well [28], [39], [24], [27]. We identified widespread left hemispheric involvement, starting 59 from 325 ms after word onset in the temporal lobe and rapidly spreading to anterior 60 areas.…”

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Sensory-modality independent activation of the brain network for language

Arana

Marquand

Hultén

et al. 2019

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The 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.Introduction 1 Language can be realized in different modalities: amongst others through writing or 2 in speech. Depending on whether the sensory input modality is visual or auditory, 3 different dedicated networks of brain areas are activated in order to derive meaning 4 from the physical stimulus. Besides the obvious differences in the recruitment of brain 5 circuits that process low-level sensory information, differences in linguistic features across 6 sensory modalities prompt a differential activation of brain areas involved in higher-order 7 1/30 processing as well. For instance, speech is enriched with meaningful prosodic cues, 8 but also requires a coarticulated signal to be parsed into individual words. Written 9 text contains cues in the form of punctuation and spaces, and has the advantage of 10 instantaneous availability of full information compared to the temporally unfolding nature 11 of speech. If text is presented word-by-word, as was done in the present as well as many 12 previous studies, the temporal structure of auditory stimulation can be approximated. 13Nonetheless, the auditory information necessary for word recognition is still temporally 14 distributed, whereas in the visual modality, the entire wordform is instantly available 15 on screen.These, and other, differences are paralleled in the brain's response, and thus 16 the sensory modality in which language stimuli are presented determines the dominant 17 spatiotemporal patterns that will be elic...

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Robust neuronal oscillatory entrainment to speech displays individual variation in lateralisation

Cited by 12 publications

References 44 publications

A hierarchy of linguistic predictions during natural language comprehension

A hierarchy of linguistic predictions during natural language comprehension

Balancing exogenous and endogenous cortical rhythms for speech and language requires a lot of entraining: a commentary on Meyer, Sun & Martin (2020)

Sensory-modality independent activation of the brain network for language

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