Corticomuscular Coherence Is Tuned to the Spontaneous Rhythmicity of Speech at 2–3 Hz

Ruspantini, Irene; Saarinen, Timo; Belardinelli, Paolo; Jalava, Antti; Parviainen, Tiina; Kujala, Janne V.; Salmelin, Riitta

doi:10.1523/jneurosci.3191-11.2012

Cited by 45 publications

(50 citation statements)

References 40 publications

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“…While natural human speech is not strictly rhythmic, continuous natural speech is characterized by quasi-periodic modulation in sound amplitude and orofacial movements in the 3-to 8-Hz range, a modulation most easily detected in the coherence between speech amplitude and neural measures of speech control (Alexandrou et al, 2016;Ruspantini et al, 2012). …”

Section: Discussionmentioning

confidence: 99%

Rhythmic Continuous-Time Coding in the Songbird Analog of Vocal Motor Cortex

Lynch

Okubo

Hanuschkin

et al. 2016

Neuron

154

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Songbirds learn and produce complex sequences of vocal gestures. Adult birdsong requires premotor nucleus HVC, in which projection neurons (PNs) burst sparsely at stereotyped times in the song. It has been hypothesized that PN bursts, as a population, form a continuous sequence, while a different model of HVC function proposes that both HVC PN and interneuron activity is tightly organized around motor gestures. Using a large dataset of PNs and interneurons recorded in singing birds, we test several predictions of these models. We find that PN bursts in adult birds are continuously and nearly uniformly distributed throughout song. However, we also find that PN and interneuron firing rates exhibit significant 10-Hz rhythmicity locked to song syllables, peaking prior to syllable onsets and suppressed prior to offsets-a pattern that predominates PN and interneuron activity in HVC during early stages of vocal learning.

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Section: Discussionmentioning

confidence: 99%

Rhythmic Continuous-Time Coding in the Songbird Analog of Vocal Motor Cortex

Lynch

Okubo

Hanuschkin

et al. 2016

Neuron

154

View full text Add to dashboard Cite

show abstract

“…In particular, as the muscle spindles of the tongue are highly developed in humans compared with those in other primates, proprioception from the tongue muscle spindles in humans may play an important role in speech production. Ruspantini et al (2012) reported that the low oscillatory frequency related to proprioceptive afferent feedback from the mouth muscles might play an important role in the smooth and sophisticated oral movements generated during word production. Moreover, the low-CMC related to proprioception may play critical role for keeping tongue position.…”

Section: Generator Mechanism Of the Low-cmcmentioning

confidence: 99%

Cortico-muscular synchronization by proprioceptive afferents from the tongue muscles during isometric tongue protrusion

et al. 2016

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Tongue movements contribute to oral functions including swallowing, vocalizing, and breathing. Fine tongue movements are regulated through efferent and afferent connections between the cortex and tongue. It has been demonstrated that cortico-muscular coherence (CMC) is reflected at two frequency bands during isometric tongue protrusions: the beta (β) band at 15-35 Hz and the low-frequency band at 2-10 Hz. The CMC at the β band (β-CMC) reflects motor commands from the primary motor cortex (M1) to the tongue muscles through hypoglossal motoneuron pools. However, the generator mechanism of the CMC at the low-frequency band (low-CMC) remains unknown. Here, we evaluated the mechanism of low-CMC during isometric tongue protrusion using magnetoencephalography (MEG). Somatosensory evoked fields (SEFs) were also recorded following electrical tongue stimulation. Significant low-CMC and β-CMC were observed over both hemispheres for each side of the tongue.Time-domain analysis showed that the MEG signal followed the electromyography signal for low-CMC, which was contrary to the finding that the MEG signal preceded the electromyography signal for β-CMC. The mean conduction time from the tongue to the cortex was not significantly different between the low-CMC (mean, 80.9 ms) and SEFs (mean, 71.1 ms). The cortical sources of low-CMC were located significantly posterior (mean, 10.1 mm) to the sources of β-CMC in M1, but were in the same area as tongue SEFs in the primary somatosensory cortex (S1). These results reveal that the low-CMC may be driven by proprioceptive afferents from the tongue muscles to S1, and that the oscillatory interaction was derived from each side of the tongue to both hemispheres. Oscillatory proprioceptive feedback from the tongue muscles may aid in the coordination of sophisticated tongue movements in humans.

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“…As previously explained, we disregard much of this variability; yet, not all results are readily usable in the context of the current discussion. We exclude the results from Gehrig et al (2012), Resnik et al (2014), and Ruspantini et al (2012), as their window(s) of analysis were ≥1 s (see their methods) and Salmelin et al (1994) because the results from their early methods of source localisation are not easily placed in our "cartoon" of cortical areas (see Figure 1). These exclusions leave 142 activities in 14 papers as being eligible for inclusion in our meta-analysis.…”

Section: Original Reportsmentioning

confidence: 99%

“…The largest group of studies (but not a majority) focuses on motor functions (e.g. Ruspantini et al, 2012;Salmelin et al, 2000). Despite this diversity, the processes identified by the authors can be grouped into broad categories corresponding to canonical stages in language processing.…”

Section: Dynamics Of Function -The Original Authors' Interpretationmentioning

confidence: 99%

On the cortical dynamics of word production: a review of the MEG evidence

Munding

Dubarry

Alario

2015

Language, Cognition and Neuroscience

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International audienceWord production has been investigated using magnetoencephalography [MEG] for 20 years. We perform a review and meta-analysis of MEG studies of word production published in the last 20 years (1994-2014). We assess significant findings with the goals of gauging spatial and temporal resolution, evaluating the between-studies consistency of the cortical response, and the reliability of cognitive inferences made from these findings. We use the author's own attribution of activity to function and current serial and interactive models to scaffold our analysis. Despite current data trending towards seriality in the dynamics of component functions of speech, no strong claims are warranted regarding the serial or parallel nature of cognitive processes. We suggest that future studies might employ standardised protocols and analyses, and report their results more comprehensively to make inferring cognitive function and relating MEG data to psycholinguistic models more efficient

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Corticomuscular Coherence Is Tuned to the Spontaneous Rhythmicity of Speech at 2–3 Hz

Cited by 45 publications

References 40 publications

Rhythmic Continuous-Time Coding in the Songbird Analog of Vocal Motor Cortex

Rhythmic Continuous-Time Coding in the Songbird Analog of Vocal Motor Cortex

Cortico-muscular synchronization by proprioceptive afferents from the tongue muscles during isometric tongue protrusion

On the cortical dynamics of word production: a review of the MEG evidence

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