Causal evidence for a coordinated temporal interplay within the language network

Schroën, Joëlle A. M.; Gunter, Thomas C.; Numssen, Ole; Kroczek, Leon O. H.; Hartwigsen, Gesa; Friederici, Angela D.

doi:10.1073/pnas.2306279120

Cited by 5 publications

(4 citation statements)

References 148 publications

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“…3e ). Whereas structures showing coupled fluctuations in entrainment are typically associated with processing of speech 28–31 (and therefore may reflect attention to sensory input), those with corresponding α-fluctuations involve regions associated with fronto-parietal attention networks 32,33 , but also the default mode network 33,34 . Together, these results imply that fluctuations in opposing attentional modes may stem from an interaction between distinct cortical networks, one associated with active processing of external stimuli (i.e., the speech network), and the other concerned with up- and down-regulation of processing resources via inhibitory α-oscillations.…”

Section: Resultsmentioning

confidence: 99%

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Opposing neural processing modes alternate rhythmically during sustained auditory attention

Kasten,

Busson,

Zoefel

2023

Preprint

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When confronted with continuous tasks, humans show spontaneous fluctuations in performance, putatively caused by varying attentional resources allocated to process external information. If neural resources are used to process other, presumably “internal” information, sensory input can be missed and explain an apparent dichotomy of “internal” versus “external” attention.Each of these opposing attentional modes might have their own distinct neural signature. For instance, α-oscillations (∼10-Hz) have been linked to a suppression of sensory information and might therefore reflect a state of internal attention. Indeed, in auditory cortex of macaque monkeys, periods with strong α-oscillations and reduced responses to sounds alternate with periods in which the opposite pattern occurs. In the current study, we extracted neural signatures of internal and external attention in human electroencephalography (EEG) - α-oscillations and neural entrainment, respectively. We then tested whether they exhibit structured fluctuations over time, when listeners attended to an ecologically relevant stimulus like speech, and completed a task that required full and continuous attention.Results showed an antagonistic relation between spontaneous α-oscillations and neural activity synchronized to speech. These opposing neural modes underwent slow, periodic fluctuations around ∼0.07 Hz that were strikingly similar to those observed in non-human primates, and related to the successful detection of auditory targets. Our study might have tapped into a general attentional mechanism that is conserved across species and has important implications for situations in which sustained attention to sensory information is critical.SignificanceUnderstanding fluctuations in sustained attention is crucial for a wide variety of everyday activities, e.g., in traffic, education or safety monitoring. Lapses in attention can negatively affect outcomes in these tasks, sometimes with severe consequences. Here we demonstrate that auditory sustained attention fluctuates between an external mode favoring the processing of sensory information and an internal mode, where sensory information is ignored. These attentional modes have their own neural signatures and alternate with an inherent rhythmicity that can be traced in the human electro-encephalogram. Our results may be leveraged to predict attentional fluctuations, optimize critical system designs or tailor interventional approaches to improve sustained attention.

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Section: Resultsmentioning

confidence: 99%

“…4e ). Whereas structures showing coupled fluctuations in entrainment are typically associated with processing of speech 33–36 (and therefore may reflect attention to sensory input), those with corresponding α-fluctuations involve regions associated with fronto-parietal attention networks 37,38 , but also the default mode network 38,39 .…”

Section: Resultsmentioning

confidence: 99%

Opposing neural processing modes alternate rhythmically during sustained auditory attention

Kasten,

Busson,

Zoefel

2023

Preprint

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“…Using similar method in a reading task, Schoffelen et al (2017) found feedforward connection from pMTG to IFG and feedback and feedforward connections between IFG and aMTG. A recent study (Schroen et al, 2023) using a subset of our stimulus material investigated temporo-frontal causal influences with a combined transcranial magnetic stimulation and electroencephalography approach. Interestingly, using this completely different approach, they also observed early feedforward influences from left pSTG to left IFG and late feedback influences (300-500ms) from left IFG to left pSTG.…”

Section: Discussionmentioning

confidence: 99%

Characterizing directional dynamics of semantic prediction based on inter-regional temporal generalization

Mamashli,

Khan,

Hatamimajoumerd

et al. 2024

Preprint

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The event-related potential/field component N400(m) has been widely used as a neural index for semantic prediction. It has long been hypothesized that feedback information from inferior frontal areas plays a critical role in generating the N400. However, due to limitations in causal connectivity estimation, direct testing of this hypothesis has remained difficult. Here, magnetoencephalography (MEG) data was obtained during a classic N400 paradigm where the semantic predictability of a fixed target noun was manipulated in simple German sentences. To estimate causality, we implemented a novel approach based on machine learning and temporal generalization to estimate the effect of inferior frontal gyrus (IFG) on temporal areas. In this method, a support vector machine (SVM) classifier is trained on each time point of the neural activity in IFG to classify less predicted (LP) and highly predicted (HP) nouns and then tested on all time points of superior/middle temporal sub-regions activity (and vice versa, to establish spatio-temporal evidence for or against causality). The decoding accuracy was significantly above chance level when the classifier was trained on IFG activity and tested on future activity in superior and middle temporal gyrus (STG/MTG). The results present new evidence for a model predictive speech comprehension where predictive IFG activity is fed back to shape subsequent activity in STG/MTG, implying a feedback mechanism in N400 generation. In combination with the also observed strong feedforward effect from left STG/MTG to IFG, our findings provide evidence of dynamic feedback and feedforward influences between IFG and temporal areas during N400 generation.

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“…Other types of studies have evaluated the interplay between nodes of the language network during specific tasks. For example, one study of concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) revealed time-and region-specific causal evidence for a bidirectional flow of activation from the left pSTG/superior temporal sulcus (STS) to the left posterior inferior frontal gyrus (pIFG) and back during auditory sentence processing, as well as interplay between left pSTG/STS and left AG [20].…”

Section: The Left-hemisphere Language Networkmentioning

confidence: 99%

Remapping and Reconnecting the Language Network after Stroke

Tilton-Bolowsky,

Stockbridge,

Hillis

2024

Brain Sciences

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Here, we review the literature on neurotypical individuals and individuals with post-stroke aphasia showing that right-hemisphere regions homologous to language network and other regions, like the right cerebellum, are activated in language tasks and support language even in healthy people. We propose that language recovery in post-stroke aphasia occurs largely by potentiating the right hemisphere network homologous to the language network and other networks that previously supported language to a lesser degree and by modulating connection strength between nodes of the right-hemisphere language network and undamaged nodes of the left-hemisphere language network. Based on this premise (supported by evidence we review), we propose that interventions should be aimed at potentiating the right-hemisphere language network through Hebbian learning or by augmenting connections between network nodes through neuroplasticity, such as non-invasive brain stimulation and perhaps modulation of neurotransmitters involved in neuroplasticity. We review aphasia treatment studies that have taken this approach. We conclude that further aphasia rehabilitation with this aim is justified.

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Causal evidence for a coordinated temporal interplay within the language network

Cited by 5 publications

References 148 publications

Opposing neural processing modes alternate rhythmically during sustained auditory attention

Opposing neural processing modes alternate rhythmically during sustained auditory attention

Characterizing directional dynamics of semantic prediction based on inter-regional temporal generalization

Remapping and Reconnecting the Language Network after Stroke

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