Frequency selectivity of persistent cortical oscillatory responses to auditory rhythmic stimulation

Lerousseau, Jacques Pesnot; Trébuchon, Agnès; Morillon, Benjamin; Schön, Daniele

doi:10.1101/834226

Cited by 6 publications

(4 citation statements)

References 108 publications

(228 reference statements)

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“…In the present work, we studied a well-characterized auditory evoked brain response, and selected analyses like frequency tracking that are unlikely to introduce artifactual oscillations (as might narrowband filtering or broad spectral analysis). Our data are consistent with prior reports of poststimulus FFR aftereffects in EEG data (Xu and Ye, 2015), and with recent data also documenting similar aftereffects from intracerebral electrode cortical recordings and cortical MEG in humans in the 60-80 Hz range, similar to the stimuli used here (Lerousseau et al, 2019;Ross et al, 2020). Taken together, these convergent findings provide strong evidence for entrainment, and our data furthermore indicate that it is a pervasive feature of auditory processing in subcortical nuclei as well as cortex.…”

Section: Discussionsupporting

confidence: 93%

Oscillatory entrainment of the Frequency Following Response in auditory cortical and subcortical structures

Coffey

Arseneau-Bruneau

Zhang

et al. 2020

Preprint

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There is much debate about the existence and function of neural oscillatory entrainment mechanisms in the auditory system. The frequency-following response (FFR) is an index of neural periodicity encoding that can provide a vehicle to study entrainment in frequency ranges relevant to speech and music processing. Criteria for entrainment include the presence of post-stimulus oscillations and phase alignment between stimulus and endogenous activity. To test the hypothesis of entrainment, in experiment 1 we collected FFR data to a repeated syllable using magneto- (MEG) and electroencephalography in 20 healthy adults. We observed significant oscillatory activity after stimulus offset in auditory cortex and subcortical auditory nuclei, consistent with entrainment. In these structures the FFR fundamental frequency converged from a lower value over 100 ms to the stimulus frequency, consistent with phase alignment, and diverged to a lower value after offset, consistent with relaxation to a preferred frequency. In experiment 2, we tested how transitions between stimulus frequencies affected the MEG-FFR to a train of pure-tone pairs in 30 adults. We found that the FFR was affected by the frequency of the preceding tone for up to 40 ms at subcortical levels, and even longer durations at cortical levels. Our results suggest that oscillatory entrainment may be an integral part of periodic sound representation throughout the auditory neuraxis. The functional role of this mechanism is unknown, but it could serve as a fine-scale temporal predictor for frequency information, enhancing stability and reducing susceptibility to degradation that could be useful in real-life noisy environments.

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Section: Discussionsupporting

confidence: 93%

Oscillatory entrainment of the Frequency Following Response in auditory cortical and subcortical structures

Coffey

Arseneau-Bruneau

Zhang

et al. 2020

Preprint

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“…In any event, the across-frequency band results for beta and alpha combined are further in line with a recent related report by Griffiths et al (2019), who also showed an effect spanning both frequency bands, although at a slower stimulation rate [38]. Directly relevant, most recent MEG work by Lerousseau and co-workers [50] presents with yet differing results with respect to the oscillatory modulations in the relevant frequency bands in question. In their study of passive listening to a regular beat in the relevant range, in fact of identical tempo to ours (2.5 Hz), the authors found no beat-based modulation in the beta nor in the alpha band, but rather an overall suppression of activity across both bands in the auditory cortex.…”

Section: Beat-based Modulations In Oscillatory Powersupporting

confidence: 90%

Fourier SPoC: A customised machine-learning analysis pipeline for auditory beat-based entrainment in the MEG

Brandl

Haumann²,

Radloff³

et al. 2021

Preprint

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We propose here (the informed use) of a customised, data-driven machine-learning pipeline to analyse magnetoencephalography (MEG) in a theoretical source space, with respect to the processing of a regular beat. This hypothesis- and data-driven analysis pipeline allows us to extract the maximally relevant components in MEG source-space, with respect to the oscillatory power in the frequency band of interest and, most importantly, the beat-related modulation of that power. Our pipeline combines Spatio-Spectral Decomposition as a first step to seek activity in the frequency band of interest (SSD, [1]) with a Source Power Co-modulation analysis (SPoC; [2]), which extracts those components that maximally entrain their activity with the given target function, that is here with the periodicity of the beat in the frequency domain (hence, f-SPoC). MEG data (102 magnetometers) from 28 participants passively listening to a 5-min long regular tone sequence with a 400 ms beat period (the “target function” for SPoC) were segmented into epochs of two beat periods each to guarantee a sufficiently long time window. As a comparison pipeline to SSD and f-SpoC, we carried out a state-of-the-art cluster-based permutation analysis (CBPA, [3]). The time-frequency analysis (TFA) of the extracted activity showed clear regular patterns of periodically occurring peaks and troughs across the alpha and beta band (8-20 Hz) in the f-SPoC but not in the CBPA results, and both the depth and the specificity of modulation to the beat frequency yielded a significant advantage. Future applications of this pipeline will address target the relevance to behaviour and inform analogous analyses in the EEG, in order to finally work toward addressing dysfunctions in beat-based timing and their consequences.Author summaryWhen listening to a regular beat, oscillations in the brain have been shown to synchronise with the frequency of that given beat. This phenomenon is called entrainment and has in previous brain-imaging studies been shown in the form of one peak and trough per beat cycle in a range of frequency bands within 15-25 Hz (beta band). Using machine-learning techniques, we designed an analysis pipeline based on Source-Power Co-Modulation (SPoC) that enables us to extract spatial components in MEG recordings that show these synchronisation effects very clearly especially across 8-20 Hz. This approach requires no anatomical knowledge of the individual or even the average brain, it is purely data driven and can be applied in a hypothesis-driven fashion with respect to the “function” that we expect the brain to entrain with and the frequency band within which we expect to see this entrainment. We here apply our customised pipeline using “f-SPoC” to MEG recordings from 28 participants passively listening to a 5-min long tone sequence with a regular 2.5 Hz beat. In comparison to a cluster-based permutation analysis (CBPA) which finds sensors that show statistically significant power modulations across participants, our individually extracted f-SPoC components find a much stronger and clearer pattern of peaks and troughs within one beat cycle. In future work, this pipeline can be implemented to tackle more complex “target functions” like speech and music, and might pave the way toward rhythm-based rehabilitation strategies.

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“…These findings are essential in showing that neural entrainment is not solely a bottom-up brain response to exogenous periodicities, it also reflects an endogenous temporal structure that is experienced by the listener. In fact, oscillatory dynamics can be measured in the absence of exogenous stimulation and resonate during and after rhythmic (Cason et al, 2015;Falk et al, 2017;Pesnot Lerousseau et al, 2021) and non-rhythmic (Teng et al, 2018) stimulation. Such intrinsic spontaneous oscillators support the biological and psychological needs for adaptability and stability.…”

Section: Modulation Of Endogenous Oscillations: Uncoupled Couplingmentioning

confidence: 99%

Psychological and neuroscientific foundations of rhythms and timing

Doelling¹,

Herbst²,

Arnal³

et al. 2022

Preprint

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Cultural artefacts, such as dance and music, are characterized by temporal properties, broadly referred to as rhythms. The temporal structures that emerge when individuals synchronize their movements provide a sense of togetherness and common fate, even if individuals can readily tune in and out of this shared temporal space. In this chapter, we concisely discuss the endogenous and exogenous factors contributing to the emergence of brain rhythms and rhythmic behaviors, and how their interplay contributes to sophisticated forms of expressions in humans. The capacity for coupling and uncoupling voluntarily from external rhythms creates a potential tension between our environment (exogenously driven) and our internal state (endogenously driven) that can be exploited for artistic benefit, in the form of surprisal.

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Frequency selectivity of persistent cortical oscillatory responses to auditory rhythmic stimulation

Cited by 6 publications

References 108 publications

Oscillatory entrainment of the Frequency Following Response in auditory cortical and subcortical structures

Oscillatory entrainment of the Frequency Following Response in auditory cortical and subcortical structures

Fourier SPoC: A customised machine-learning analysis pipeline for auditory beat-based entrainment in the MEG

Psychological and neuroscientific foundations of rhythms and timing

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