Frontal Top-Down Signals Increase Coupling of Auditory Low-Frequency Oscillations to Continuous Speech in Human Listeners

Park, Hyojin; Ince, Robin A. A.; Schyns, Philippe G.; Thut, Gregor; Groß, Joachim

doi:10.1016/j.cub.2015.04.049

Cited by 344 publications

(446 citation statements)

References 29 publications

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“…Given that exogenous stimulation induces a strong phase alignment (Fig. S3 B and C), we speculate that this could have masked frontal contributions (36,37). Our findings are also in line with the proposal that the absolute voltage gradient might be a better predictor of instantaneous cortical excitability than power or phase information of bandlimited signals (38).…”

Section: Discussionsupporting

confidence: 89%

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Prefrontal cortex modulates posterior alpha oscillations during top-down guided visual perception

Helfrich

Huang

Wilson

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

103

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Conscious visual perception is proposed to arise from the selective synchronization of functionally specialized but widely distributed cortical areas. It has been suggested that different frequency bands index distinct canonical computations. Here, we probed visual perception on a fine-grained temporal scale to study the oscillatory dynamics supporting prefrontal-dependent sensory processing. We tested whether a predictive context that was embedded in a rapid visual stream modulated the perception of a subsequent near-threshold target. The rapid stream was presented either rhythmically at 10 Hz, to entrain parietooccipital alpha oscillations, or arrhythmically. We identified a 2-to 4-Hz delta signature that modulated posterior alpha activity and behavior during predictive trials. Importantly, deltamediated top-down control diminished the behavioral effects of bottom-up alpha entrainment. Simultaneous source-reconstructed EEG and cross-frequency directionality analyses revealed that this delta activity originated from prefrontal areas and modulated posterior alpha power. Taken together, this study presents converging behavioral and electrophysiological evidence for frontal deltamediated top-down control of posterior alpha activity, selectively facilitating visual perception.top-down control | directional cross-frequency coupling | prefrontal cortex | alpha oscillations | phase-amplitude coupling V isual perception is flexible, selective, and rapidly integrates sensory evidence with endogenous high-level expectations and predictions (1, 2). It has been suggested that rhythmic brain activity constitutes a key mechanism to coordinate information flow in the human cerebral cortex by transiently forming task-relevant largescale networks (1). However, it is currently unclear how contextual information is dynamically integrated to support visual perception. Numerous studies have shown that visual perception critically depends on prestimulus alpha-band (8-12 Hz) activity (3-7). The gating-by-inhibition hypothesis postulates that alpha serves as a mechanism to route information to task-relevant cortical sites (8) but might also be under top-down control (6, 7). However, it is currently unclear which cortical regions and mechanisms mediate the directed top-down control of alpha oscillations (2). It has been suggested that slow-frequency activity in the delta range (<5 Hz) might reflect a mechanism for endogenous attentional selection and predictions (9, 10). In particular, endogenous low-frequency entrainment is thought to reflect a substrate of top-down processing (11)(12)(13)(14). Importantly, endogenous entrainment does not require rhythmicity in the input stream but reflects an intrinsic mechanism to enable predictions (15). Several studies have demonstrated that visual perception cycles as a function of the alpha phase but only a few reports have demonstrated that multiple rhythms modulate behavior on a fine-grained temporal scale (5,(16)(17)(18)(19).At present, it is uncertain how different temporal scales interact t...

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Section: Discussionsupporting

confidence: 89%

“…Previous studies in the auditory domain had localized the origin of the low-frequency activity to sensory areas and not frontal regions (13,14,35) but were confounded by the presentation rate, which likely evoked activity (14,35,36). Given that exogenous stimulation induces a strong phase alignment (Fig.…”

Section: Discussionmentioning

confidence: 98%

Prefrontal cortex modulates posterior alpha oscillations during top-down guided visual perception

Helfrich

Huang

Wilson

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

103

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“…To evaluate the performance of the continuous–continuous GCMI estimator (Section 3.1), we consider MEG data collected from a single subject within a continuous design with an auditory speech stimulus [Gross et al, 2013; Park et al, 2015]. For simplicity we focus here on a sensor‐level time‐domain analysis.…”

Section: Resultsmentioning

confidence: 99%

“…MI reveals a functional property of the system that might change with different experimental conditions, for example with the rhythmic structure of speech stimuli [Kayser et al, 2015] or spatial attention [Guggenmos et al, 2015; Saproo and Serences, 2010]. Functional connectivity, measured with transfer entropy (DI), has been shown to be affected by the intelligibility of speech [Park et al, 2015]. When considering MI computed in different experimental conditions accurate bias correction is important because bias may not be equal in each condition (for example due to differing numbers of samples, or different degrees of signal autocorrelation).…”

Section: Discussionmentioning

confidence: 99%

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula

Ince

Giordano

Kayser

et al. 2016

Human Brain Mapping

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265

298

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We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open‐source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541–1573, 2017. © 2016 Wiley Periodicals, Inc.

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“…The volume envelope of speech fluctuates at low frequencies (< 8 Hz), decreasing at boundaries between syllables, words, and phrases. When people listen to speech, neural oscillations in the delta (1-4 Hz) and theta (4)(5)(6)(7)(8) bands become entrained to these fluctuations in volume (1)(2)(3)(4).…”

mentioning

confidence: 99%

Visual cortex entrains to sign language

Brookshire

Nusbaum

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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Despite immense variability across languages, people can learn to understand any human language, spoken or signed. What neural mechanisms allow people to comprehend language across sensory modalities? When people listen to speech, electrophysiological oscillations in auditory cortex entrain to slow (<8 Hz) fluctuations in the acoustic envelope. Entrainment to the speech envelope may reflect mechanisms specialized for auditory perception. Alternatively, flexible entrainment may be a general-purpose cortical mechanism that optimizes sensitivity to rhythmic information regardless of modality. Here, we test these proposals by examining cortical coherence to visual information in sign language. First, we develop a metric to quantify visual change over time. We find quasiperiodic fluctuations in sign language, characterized by lower frequencies than fluctuations in speech. Next, we test for entrainment of neural oscillations to visual change in sign language, using electroencephalography (EEG) in fluent speakers of American Sign Language (ASL) as they watch videos in ASL. We find significant cortical entrainment to visual oscillations in sign language <5 Hz, peaking at ∼1 Hz. Coherence to sign is strongest over occipital and parietal cortex, in contrast to speech, where coherence is strongest over the auditory cortex. Nonsigners also show coherence to sign language, but entrainment at frontal sites is reduced relative to fluent signers. These results demonstrate that flexible cortical entrainment to language does not depend on neural processes that are specific to auditory speech perception. Low-frequency oscillatory entrainment may reflect a general cortical mechanism that maximizes sensitivity to informational peaks in time-varying signals.sign language | cortical entrainment | oscillations | EEG L anguages differ dramatically from one another, yet people can learn to understand any natural language. What neural mechanisms allow humans to understand the vast diversity of languages and to distinguish linguistic signal from noise? One mechanism that has been implicated in language comprehension is neural entrainment to the volume envelope of speech. The volume envelope of speech fluctuates at low frequencies (< 8 Hz), decreasing at boundaries between syllables, words, and phrases. When people listen to speech, neural oscillations in the delta (1-4 Hz) and theta (4-8 Hz) bands become entrained to these fluctuations in volume (1-4).Entrainment to the volume envelope may represent an active neural mechanism to boost perceptual sensitivity to rhythmic stimuli (2, 5-7). Although entrainment is partly driven by bottom-up features of the stimulus (8-10), it also depends on top-down signals to auditory cortex from other brain areas. Auditory entrainment is strengthened when people see congruent visual and auditory information (11,12) and is modulated by attention (13) and by top-down signals from frontal cortex (4, 14).Cortical entrainment is proposed to perform a key role in speech comprehension, such as segmenting out sylla...

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Frontal Top-Down Signals Increase Coupling of Auditory Low-Frequency Oscillations to Continuous Speech in Human Listeners

Cited by 344 publications

References 29 publications

Prefrontal cortex modulates posterior alpha oscillations during top-down guided visual perception

Prefrontal cortex modulates posterior alpha oscillations during top-down guided visual perception

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula

Visual cortex entrains to sign language

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