Speech encoding by coupled cortical theta and gamma oscillations

High-Gamma Activity Is Coupled to Low-Gamma Oscillations in Precentral Cortices and Modulates with Movement and Speech

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger-flexion or word-reading tasks. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

Cross-linguistic and acoustic-driven effects on multiscale neural synchrony to stress rhythms

We investigated how neural oscillations code the hierarchical nature of stress rhythms in speech and how stress processing varies with language experience. By measuring phase synchrony of multilevel EEG-acoustic tracking and intra-brain cross-frequency coupling, we show the encoding of stress involves different neural signatures (delta rhythms = stress foot rate; theta rhythms = syllable rate), is stronger for amplitude vs. duration stress cues, and induces nested delta-theta coherence mirroring the stress-syllable hierarchy in speech. Only native English, but not Mandarin, speakers exhibited enhanced neural entrainment at central stress (2 Hz) and syllable (4 Hz) rates intrinsic to natural English. English individuals with superior cortical-stress tracking capabilities also displayed stronger neural hierarchical coherence, highlighting a nuanced interplay between internal nesting of brain rhythms and external entrainment rooted in language-specific speech rhythms. Our cross-language findings reveal brain-speech synchronization is not purely a "bottom-up" but benefits from "top-down" processing from listeners' language-specific experience.

Speech Reception in Young Children with Autism Is Selectively Indexed by a Neural Oscillation Coupling Anomaly

Communication difficulties are one of the core criteria in diagnosing autism spectrum disorder (ASD), and are often characterized by speech reception difficulties, whose biological underpinnings are not yet identified. This deficit could denote atypical neuronal ensemble activity, as reflected by neural oscillations. Atypical cross-frequency oscillation coupling, in particular, could disrupt the joint tracking and prediction of dynamic acoustic stimuli, a dual process that is essential for speech comprehension. Whether such oscillatory anomalies already exist in very young children with ASD, and with what specificity they relate to individual language reception capacity is unknown. We collected neural activity data using electroencephalography (EEG) in 64 very young children with and without ASD (mean age 3; 17 females, 47 males) while they were exposed to naturalistic-continuous speech. EEG power of frequency bands typically associated with phrase-level chunking (δ, 1-3 Hz), phonemic encoding (low-γ, 25-35 Hz), and top-down control (β, 12-20 Hz) were markedly reduced in ASD relative to typically developing (TD) children. Speech neural tracking by δ and θ (4-8 Hz) oscillations was also weaker in ASD compared with TD children. After controlling gaze-pattern differences, we found that the classical θ/γ coupling was replaced by an atypical β/γ coupling in children with ASD. This anomaly was the single most specific predictor of individual speech reception difficulties in ASD children. These findings suggest that early interventions (e.g., neurostimulation) targeting the disruption of β/γ coupling and the upregulation of θ/γ coupling could improve speech processing coordination in young children with ASD and help them engage in oral interactions.SIGNIFICANCE STATEMENT Very young children already present marked alterations of neural oscillatory activity in response to natural speech at the time of autism spectrum disorder (ASD) diagnosis. Hierarchical processing of phonemic-range and syllabic-range information (θ/γ coupling) is disrupted in ASD children. Abnormal bottom-up (low-γ) and top-down (low-β) coordination specifically predicts speech reception deficits in very young ASD children, and no other cognitive deficit.

Intergenerational choral singing to improve communication outcomes in Parkinson's disease: Development of a theoretical framework and an integrated measurement tool

Purpose: This study presented an initial step towards developing the evidence base for intergenerational choral singing as a communication-focussed rehabilitative approach for Parkinson's disease (PD).Method: A theoretical framework was established to conceptualise the rehabilitative effect of intergenerational choral singing on four domains of communication impairments - motor drive, timing mechanism, sensorimotor integration, higher-level cognitive and affective functions - as well as activity/participation, and quality of life. A computer-assisted multidimensional acoustic analysis was developed to objectively assess the targeted domains of communication impairments. Voice Handicap Index and the World Health Organization's Quality of Life assessment-abbreviated version were used to obtain patient-reported outcomes at the activity/participation and quality of life levels. As a proof of concept, a single subject with PD was recruited to participate in 9 weekly 1-h intergenerational choir rehearsals. The subject was assessed before, 1 week post, and 8 weeks post-choir.Result: Notable trends of improvement were observed in multiple domains of communication impairments at 1 week post-choir. Some improvements were maintained at 8 weeks post-choir. Patient-reported outcomes exhibited limited pre-post changes.Conclusion: This study provided the theoretical groundwork and an empirical measurement tool for future validation of intergenerational choral singing as a novel rehabilitation for PD.

Case report: Neural timing deficits prevalent in developmental disorders, aging, and concussions remediated rapidly by movement discrimination exercises

Background

The substantial evidence that neural timing deficits are prevalent in developmental disorders, aging, and concussions resulting from a Traumatic Brain Injury (TBI) is presented.

Objective

When these timing deficits are remediated using low-level movement-discrimination training, then high-level cognitive skills, including reading, attention, processing speed, problem solving, and working memory improve rapidly and effectively.

Methods

In addition to the substantial evidence published previously, new evidence based on a neural correlate, MagnetoEncephalography physiological recordings, on an adult dyslexic, and neuropsychological tests on this dyslexic subject and an older adult were measured before and after 8-weeks of contrast sensitivity-based left-right movement-discrimination exercises were completed.

Results

The neuropsychological tests found large improvements in reading, selective and sustained attention, processing speed, working memory, and problem-solving skills, never before found after such a short period of training. Moreover, these improvements were found 4 years later for older adult. Substantial MEG signal increases in visual Motion, Attention, and Memory/Executive Control Networks were observed following training on contrast sensitivity-based left-right movement-discrimination. Improving the function of magnocells using figure/ground movement-discrimination at both low and high levels in dorsal stream: (1) improved both feedforward and feedback pathways to modulate attention by enhancing coupled theta/gamma and alpha/gamma oscillations, (2) is adaptive, and (3) incorporated cycles of feedback and reward at multiple levels.

Conclusion

What emerges from multiple studies is the essential role of timing deficits in the dorsal stream that are prevalent in developmental disorders like dyslexia, in aging, and following a TBI. Training visual dorsal stream function at low levels significantly improved high-level cognitive functions, including processing speed, selective and sustained attention, both auditory and visual working memory, problem solving, and reading fluency. A paradigm shift for treating cognitive impairments in developmental disorders, aging, and concussions is crucial. Remediating the neural timing deficits of low-level dorsal pathways, thereby improving both feedforward and feedback pathways, before cognitive exercises to improve specific cognitive skills provides the most rapid and effective methods to improve cognitive skills. Moreover, this adaptive training with substantial feedback shows cognitive transfer to tasks not trained on, significantly improving a person's quality of life rapidly and effectively.

DIVA Meets EEG: Model Validation Using Formant-Shift Reflex

The neurocomputational model 'Directions into Velocities of Articulators' (DIVA) was developed to account for various aspects of normal and disordered speech production and acquisition. The neural substrates of DIVA were established through functional magnetic resonance imaging (fMRI), providing physiological validation of the model. This study introduces DIVA_EEG an extension of DIVA that utilizes electroencephalography (EEG) to leverage the high temporal resolution and broad availability of EEG over fMRI. For the development of DIVA_EEG, EEG-like signals were derived from original equations describing the activity of the different DIVA maps. Synthetic EEG associated with the utterance of syllables was generated when both unperturbed and perturbed auditory feedback (first formant perturbations) were simulated. The cortical activation maps derived from synthetic EEG closely resembled those of the original DIVA model. To validate DIVA_EEG, the EEG of individuals with typical voices (N = 30) was acquired during an altered auditory feedback paradigm. The resulting empirical brain activity maps significantly overlapped with those predicted by DIVA_EEG. In conjunction with other recent model extensions, DIVA_EEG lays the foundations for constructing a complete neurocomputational framework to tackle vocal and speech disorders, which can guide model-driven personalized interventions.

Effects of Syllable Rate on Neuro-Behavioral Synchronization Across Modalities: Brain Oscillations and Speech Productions

Considerable work suggests the dominant syllable rhythm of the acoustic envelope is remarkably similar across languages (∼4-5 Hz) and that oscillatory brain activity tracks these quasiperiodic rhythms to facilitate speech processing. However, whether this fundamental periodicity represents a common organizing principle in both auditory and motor systems involved in speech has not been explicitly tested. To evaluate relations between entrainment in the perceptual and production domains, we measured individuals' (i) neuroacoustic tracking of the EEG to speech trains and their (ii) simultaneous and non-simultaneous productions synchronized to syllable rates between 2.5 and 8.5 Hz. Productions made without concurrent auditory presentation isolated motor speech functions more purely. We show that neural synchronization flexibly adapts to the heard stimuli in a rate-dependent manner, but that phase locking is boosted near ∼4.5 Hz, the purported dominant rate of speech. Cued speech productions (recruit sensorimotor interaction) were optimal between 2.5 and 4.5 Hz, suggesting a low-frequency constraint on motor output and/or sensorimotor integration. In contrast, "pure" motor productions (without concurrent sound cues) were most precisely generated at rates of 4.5 and 5.5 Hz, paralleling the neuroacoustic data. Correlations further revealed strong links between receptive (EEG) and production synchronization abilities; individuals with stronger auditory-perceptual entrainment better matched speech rhythms motorically. Together, our findings support an intimate link between exogenous and endogenous rhythmic processing that is optimized at 4-5 Hz in both auditory and motor systems. Parallels across modalities could result from dynamics of the speech motor system coupled with experience-dependent tuning of the perceptual system via the sensorimotor interface.

Acoustic correlates of the syllabic rhythm of speech: Modulation spectrum or local features of the temporal envelope

The syllable is a perceptually salient unit in speech. Since both the syllable and its acoustic correlate, i.e., the speech envelope, have a preferred range of rhythmicity between 4 and 8 Hz, it is hypothesized that theta-band neural oscillations play a major role in extracting syllables based on the envelope. A literature survey, however, reveals inconsistent evidence about the relationship between speech envelope and syllables, and the current study revisits this question by analyzing large speech corpora. It is shown that the center frequency of speech envelope, characterized by the modulation spectrum, reliably correlates with the rate of syllables only when the analysis is pooled over minutes of speech recordings. In contrast, in the time domain, a component of the speech envelope is reliably phase-locked to syllable onsets. Based on a speaker-independent model, the timing of syllable onsets explains about 24% variance of the speech envelope. These results indicate that local features in the speech envelope, instead of the modulation spectrum, are a more reliable acoustic correlate of syllables.

Theta-gamma phase amplitude coupling in a hippocampal CA1 microcircuit

Phase amplitude coupling (PAC) between slow and fast oscillations is found throughout the brain and plays important functional roles. Its neural origin remains unclear. Experimental findings are often puzzling and sometimes contradictory. Most computational models rely on pairs of pacemaker neurons or neural populations tuned at different frequencies to produce PAC. Here, using a data-driven model of a hippocampal microcircuit, we demonstrate that PAC can naturally emerge from a single feedback mechanism involving an inhibitory and excitatory neuron population, which interplay to generate theta frequency periodic bursts of higher frequency gamma. The model suggests the conditions under which a CA1 microcircuit can operate to elicit theta-gamma PAC, and highlights the modulatory role of OLM and PVBC cells, recurrent connectivity, and short term synaptic plasticity. Surprisingly, the results suggest the experimentally testable prediction that the generation of the slow population oscillation requires the fast one and cannot occur without it.

Hierarchically nested networks optimize the analysis of audiovisual speech

In conversational settings, seeing the speaker's face elicits internal predictions about the upcoming acoustic utterance. Understanding how the listener's cortical dynamics tune to the temporal statistics of audiovisual (AV) speech is thus essential. Using magnetoencephalography, we explored how large-scale frequency-specific dynamics of human brain activity adapt to AV speech delays. First, we show that the amplitude of phase-locked responses parametrically decreases with natural AV speech synchrony, a pattern that is consistent with predictive coding. Second, we show that the temporal statistics of AV speech affect large-scale oscillatory networks at multiple spatial and temporal resolutions. We demonstrate a spatial nestedness of oscillatory networks during the processing of AV speech: these oscillatory hierarchies are such that high-frequency activity (beta, gamma) is contingent on the phase response of low-frequency (delta, theta) networks. Our findings suggest that the endogenous temporal multiplexing of speech processing confers adaptability within the temporal regimes that are essential for speech comprehension.

Foreign speech sound discrimination and associative word learning lead to a fast reconfiguration of resting-state networks

Learning new words in an unfamiliar language is a complex endeavor that requires the orchestration of multiple perceptual and cognitive functions. Although the neural mechanisms governing word learning are becoming better understood, little is known about the predictive value of resting-state (RS) metrics for foreign word discrimination and word learning attainment. In addition, it is still unknown which of the multistep processes involved in word learning have the potential to rapidly reconfigure RS networks. To address these research questions, we used electroencephalography (EEG), measured forty participants, and examined scalp-based power spectra, source-based spectral density maps and functional connectivity metrics before (RS1), in between (RS2) and after (RS3) a series of tasks which are known to facilitate the acquisition of new words in a foreign language, namely word discrimination, word-referent mapping and semantic generalization. Power spectra at the scalp level consistently revealed a reconfiguration of RS networks as a function of foreign word discrimination (RS1 vs. RS2) and word learning (RS1 vs. RS3) tasks in the delta, lower and upper alpha, and upper beta frequency ranges. Otherwise, functional reconfigurations at the source level were restricted to the theta (spectral density maps) and to the lower and upper alpha frequency bands (spectral density maps and functional connectivity). Notably, scalp RS changes related to the word discrimination tasks (difference between RS2 and RS1) correlated with word discrimination abilities (upper alpha band) and semantic generalization performance (theta and upper alpha bands), whereas functional changes related to the word learning tasks (difference between RS3 and RS1) correlated with word discrimination scores (lower alpha band). Taken together, these results highlight that foreign speech sound discrimination and word learning have the potential to rapidly reconfigure RS networks at multiple functional scales.

The channel capacity of multilevel linguistic features constrains speech comprehension

Humans are expert at processing speech but how this feat is accomplished remains a major question in cognitive neuroscience. Capitalizing on the concept of channel capacity, we developed a unified measurement framework to investigate the respective influence of seven acoustic and linguistic features on speech comprehension, encompassing acoustic, sub-lexical, lexical and supra-lexical levels of description. We show that comprehension is independently impacted by all these features, but at varying degrees and with a clear dominance of the syllabic rate. Comparing comprehension of French words and sentences further reveals that when supra-lexical contextual information is present, the impact of all other features is dramatically reduced. Finally, we estimated the channel capacity associated with each linguistic feature and compared them with their generic distribution in natural speech. Our data reveal that while acoustic modulation, syllabic and phonemic rates unfold respectively at 5, 5, and 12 Hz in natural speech, they are associated with independent processing bottlenecks whose channel capacity are of 15, 15 and 35 Hz, respectively, as suggested by neurophysiological theories. They moreover point towards supra-lexical contextual information as the feature limiting the flow of natural speech. Overall, this study reveals how multilevel linguistic features constrain speech comprehension.

High-gamma activity is coupled to low-gamma oscillations in precentral cortices and modulates with movement and speech

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger movements or speaking words aloud. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

Auditory representations for long lasting sounds: Insights from event-related brain potentials and neural oscillations

The basic features of short sounds, such as frequency and intensity including their temporal dynamics, are integrated in a unitary representation. Knowledge on how our brain processes long lasting sounds is scarce. We review research utilizing the Mismatch Negativity event-related potential and neural oscillatory activity for studying representations for long lasting simple versus complex sounds such as sinusoidal tones versus speech. There is evidence for a temporal constraint in the formation of auditory representations: Auditory edges like sound onsets within long lasting sounds open a temporal window of about 350 ms in which the sounds' dynamics are integrated into a representation, while information beyond that window contributes less to that representation. This integration window segments the auditory input into short chunks. We argue that the representations established in adjacent integration windows can be concatenated into an auditory representation of a long sound, thus, overcoming the temporal constraint.

Speech onsets and sustained speech contribute differentially to delta and theta speech tracking in auditory cortex

When we attentively listen to an individual's speech, our brain activity dynamically aligns to the incoming acoustic input at multiple timescales. Although this systematic alignment between ongoing brain activity and speech in auditory brain areas is well established, the acoustic events that drive this phase-locking are not fully understood. Here, we use magnetoencephalographic recordings of 24 human participants (12 females) while they were listening to a 1 h story. We show that whereas speech-brain coupling is associated with sustained acoustic fluctuations in the speech envelope in the theta-frequency range (4-7 Hz), speech tracking in the low-frequency delta (below 1 Hz) was strongest around onsets of speech, like the beginning of a sentence. Crucially, delta tracking in bilateral auditory areas was not sustained after onsets, proposing a delta tracking during continuous speech perception that is driven by speech onsets. We conclude that both onsets and sustained components of speech contribute differentially to speech tracking in delta- and theta-frequency bands, orchestrating sampling of continuous speech. Thus, our results suggest a temporal dissociation of acoustically driven oscillatory activity in auditory areas during speech tracking, providing valuable implications for orchestration of speech tracking at multiple time scales.

Rate and oscillatory switching dynamics of a multilayer visual microcircuit model

The neocortex is organized around layered microcircuits consisting of a variety of excitatory and inhibitory neuronal types which perform rate- and oscillation-based computations. Using modeling, we show that both superficial and deep layers of the primary mouse visual cortex implement two ultrasensitive and bistable switches built on mutual inhibitory connectivity motives between somatostatin, parvalbumin, and vasoactive intestinal polypeptide cells. The switches toggle pyramidal neurons between high and low firing rate states that are synchronized across layers through translaminar connectivity. Moreover, inhibited and disinhibited states are characterized by low- and high-frequency oscillations, respectively, with layer-specific differences in frequency and power which show asymmetric changes during state transitions. These findings are consistent with a number of experimental observations and embed firing rate together with oscillatory changes within a switch interpretation of the microcircuit.

Altered brain rhythms and behaviour in the accelerated ovarian failure mouse model of human menopause

To date, potential mechanisms of menopause-related memory and cognitive deficits have not been elucidated. Therefore, we studied brain oscillations, their phase–amplitude coupling, sleep and vigilance state patterns, running wheel use and other behavioural measures in a translationally valid mouse model of menopause, the 4-vinylcyclohexene-diepoxide-induced accelerated ovarian failure. After accelerated ovarian failure, female mice show significant alterations in brain rhythms, including changes in the frequencies of θ (5–12 Hz) and γ (30–120 Hz) oscillations, a reversed phase–amplitude coupling, altered coupling of hippocampal sharp-wave ripples to medial prefrontal cortical sleep spindles and reduced δ oscillation (0.5–4 Hz) synchrony between the two regions during non-rapid eye movement sleep. In addition, we report on significant circadian variations in the frequencies of θ and γ oscillations, and massive synchronous δ oscillations during wheel running. Our results reveal novel and specific network alterations and feasible signs for diminished brain connectivity in the accelerated ovarian failure mouse model of menopause. Taken together, our results may have identified changes possibly responsible for some of the memory and cognitive deficits previously described in this model. Corresponding future studies in menopausal women could shed light on fundamental mechanisms underlying the neurological and psychiatric comorbidities present during this important transitional phase in women’s lives.

The power of rhythms: how steady-state evoked responses reveal early neurocognitive development

Electroencephalography (EEG) is a non-invasive and painless recording of cerebral activity, particularly well-suited for studying young infants, allowing the inspection of cerebral responses in a constellation of different ways. Of particular interest for developmental cognitive neuroscientists is the use of rhythmic stimulation, and the analysis of steady-state evoked potentials (SS-EPs) - an approach also known as frequency tagging. In this paper we rely on the existing SS-EP early developmental literature to illustrate the important advantages of SS-EPs for studying the developing brain. We argue that (1) the technique is both objective and predictive: the response is expected at the stimulation frequency (and/or higher harmonics), (2) its high spectral specificity makes the computed responses particularly robust to artifacts, and (3) the technique allows for short and efficient recordings, compatible with infants' limited attentional spans. We additionally provide an overview of some recent inspiring use of the SS-EP technique in adult research, in order to argue that (4) the SS-EP approach can be implemented creatively to target a wide range of cognitive and neural processes. For all these reasons, we expect SS-EPs to play an increasing role in the understanding of early cognitive processes. Finally, we provide practical guidelines for implementing and analyzing SS-EP studies.

Cortical Tracking of Sung Speech in Adults vs Infants: A Developmental Analysis

Here we duplicate a neural tracking paradigm, previously published with infants (aged 4 to 11 months), with adult participants, in order to explore potential developmental similarities and differences in entrainment. Adults listened and watched passively as nursery rhymes were sung or chanted in infant-directed speech. Whole-head EEG (128 channels) was recorded, and cortical tracking of the sung speech in the delta (0.5–4 Hz), theta (4–8 Hz) and alpha (8–12 Hz) frequency bands was computed using linear decoders (multivariate Temporal Response Function models, mTRFs). Phase-amplitude coupling (PAC) was also computed to assess whether delta and theta phases temporally organize higher-frequency amplitudes for adults in the same pattern as found in the infant brain. Similar to previous infant participants, the adults showed significant cortical tracking of the sung speech in both delta and theta bands. However, the frequencies associated with peaks in stimulus-induced spectral power (PSD) in the two populations were different. PAC was also different in the adults compared to the infants. PAC was stronger for theta- versus delta- driven coupling in adults but was equal for delta- versus theta-driven coupling in infants. Adults also showed a stimulus-induced increase in low alpha power that was absent in infants. This may suggest adult recruitment of other cognitive processes, possibly related to comprehension or attention. The comparative data suggest that while infant and adult brains utilize essentially the same cortical mechanisms to track linguistic input, the operation of and interplay between these mechanisms may change with age and language experience.

Enhancement of speech-in-noise comprehension through vibrotactile stimulation at the syllabic rate

Syllables are important building blocks of speech. They occur at a rate between 4 and 8 Hz, corresponding to the theta frequency range of neural activity in the cerebral cortex. When listening to speech, the theta activity becomes aligned to the syllabic rhythm, presumably aiding in parsing a speech signal into distinct syllables. However, this neural activity cannot only be influenced by sound, but also by somatosensory information. Here, we show that the presentation of vibrotactile signals at the syllabic rate can enhance the comprehension of speech in background noise. We further provide evidence that this multisensory enhancement of speech comprehension reflects the multisensory integration of auditory and tactile information in the auditory cortex.

Speech unfolds over distinct temporal scales, in particular, those related to the rhythm of phonemes, syllables, and words. When a person listens to continuous speech, the syllabic rhythm is tracked by neural activity in the theta frequency range. The tracking plays a functional role in speech processing: Influencing the theta activity through transcranial current stimulation, for instance, can impact speech perception. The theta-band activity in the auditory cortex can also be modulated through the somatosensory system, but the effect on speech processing has remained unclear. Here, we show that vibrotactile feedback presented at the rate of syllables can modulate and, in fact, enhance the comprehension of a speech signal in background noise. The enhancement occurs when vibrotactile pulses occur at the perceptual center of the syllables, whereas a temporal delay between the vibrotactile signals and the speech stream can lead to a lower level of speech comprehension. We further investigate the neural mechanisms underlying the audiotactile integration through electroencephalographic (EEG) recordings. We find that the audiotactile stimulation modulates the neural response to the speech rhythm, as well as the neural response to the vibrotactile pulses. The modulations of these neural activities reflect the behavioral effects on speech comprehension. Moreover, we demonstrate that speech comprehension can be predicted by particular aspects of the neural responses. Our results evidence a role of vibrotactile information for speech processing and may have applications in future auditory prosthesis.

A comparison and classification of oscillatory characteristics in speech perception and covert speech

Covert speech, the mental imagery of speaking, has been studied increasingly to understand and decode thoughts in the context of brain-computer interfaces. In studies of speech comprehension, neural oscillations are thought to play a key role in the temporal encoding of speech. However, little is known about the role of oscillations in covert speech. In this study, we investigated the oscillatory involvements in covert speech and speech perception. Data were collected from 10 participants with 64 channel EEG. Participants heard the words, 'blue' and 'orange', and subsequently mentally rehearsed them. First, continuous wavelet transform was performed on epoched signals and subsequently two-tailed t-tests between two classes were conducted to determine statistical differences in frequency and time (t-CWT). Features were also extracted using t-CWT and subsequently classified using a support vector machine. θ and γ phase amplitude coupling (PAC) was also assessed within and between tasks. All binary classifications produced accuracies significantly greater (80-90%) than chance level, supporting the use of t-CWT in determining relative oscillatory involvements. While the perception task dynamically invoked all frequencies with more prominent θ and α activity, the covert task favoured higher frequencies with significantly higher γ activity than perception. Moreover, the perception condition produced significant θ-γ PAC, corroborating a reported linkage between syllabic and phonemic sampling. Although this coupling was found to be suppressed in the covert condition, we found significant cross-task coupling between perception θ and covert speech γ. Covert speech processing appears to be largely associated with higher frequencies of EEG. Importantly, the significant cross-task coupling between speech perception and covert speech, in the absence of within-task covert speech PAC, supports the notion that the γ- and θ-bands subserve, respectively, shared and unique encoding processes across tasks.

Musical Sophistication and Speech Auditory-Motor Coupling: Easy Tests for Quick Answers

Musical training enhances auditory-motor cortex coupling, which in turn facilitates music and speech perception. How tightly the temporal processing of music and speech are intertwined is a topic of current research. We investigated the relationship between musical sophistication (Goldsmiths Musical Sophistication index, Gold-MSI) and spontaneous speech-to-speech synchronization behavior as an indirect measure of speech auditory-motor cortex coupling strength. In a group of participants (n = 196), we tested whether the outcome of the spontaneous speech-to-speech synchronization test (SSS-test) can be inferred from self-reported musical sophistication. Participants were classified as high (HIGHs) or low (LOWs) synchronizers according to the SSS-test. HIGHs scored higher than LOWs on all Gold-MSI subscales (General Score, Active Engagement, Musical Perception, Musical Training, Singing Skills), but the Emotional Attachment scale. More specifically, compared to a previously reported German-speaking sample, HIGHs overall scored higher and LOWs lower. Compared to an estimated distribution of the English-speaking general population, our sample overall scored lower, with the scores of LOWs significantly differing from the normal distribution, with scores in the ∼30th percentile. While HIGHs more often reported musical training compared to LOWs, the distribution of training instruments did not vary across groups. Importantly, even after the highly correlated subscores of the Gold-MSI were decorrelated, particularly the subscales Musical Perception and Musical Training allowed to infer the speech-to-speech synchronization behavior. The differential effects of musical perception and training were observed, with training predicting audio-motor synchronization in both groups, but perception only in the HIGHs. Our findings suggest that speech auditory-motor cortex coupling strength can be inferred from training and perceptual aspects of musical sophistication, suggesting shared mechanisms involved in speech and music perception.

On the Role of Neural Oscillations Across Timescales in Speech and Music Processing

This mini review is aimed at a clinician-scientist seeking to understand the role of oscillations in neural processing and their functional relevance in speech and music perception. We present an overview of neural oscillations, methods used to study them, and their functional relevance with respect to music processing, aging, hearing loss, and disorders affecting speech and language. We first review the oscillatory frequency bands and their associations with speech and music processing. Next we describe commonly used metrics for quantifying neural oscillations, briefly touching upon the still-debated mechanisms underpinning oscillatory alignment. Following this, we highlight key findings from research on neural oscillations in speech and music perception, as well as contributions of this work to our understanding of disordered perception in clinical populations. Finally, we conclude with a look toward the future of oscillatory research in speech and music perception, including promising methods and potential avenues for future work. We note that the intention of this mini review is not to systematically review all literature on cortical tracking of speech and music. Rather, we seek to provide the clinician-scientist with foundational information that can be used to evaluate and design research studies targeting the functional role of oscillations in speech and music processing in typical and clinical populations.

Neural auditory processing of parameterized speech envelopes

Speech perception depends highly on the neural processing of the speech envelope. Several auditory processing deficits are hypothesized to result in a reduction in fidelity of the neural representation of the speech envelope across the auditory pathway. Furthermore, this reduction in fidelity is associated with supra-threshold speech processing deficits. Investigating the mechanisms that affect the neural encoding of the speech envelope can be of great value to gain insight in the different mechanisms that account for this reduced neural representation, and to develop stimulation strategies for hearing prosthesis that aim to restore it. In this perspective, we discuss the importance of neural assessment of phase-locking to the speech envelope from an audiological view and introduce the Temporal Envelope Speech Tracking (TEMPEST) stimulus framework which enables the electrophysiological assessment of envelope processing across the auditory pathway in a systematic and standardized way. We postulate that this framework can be used to gain insight in the salience of speech-like temporal envelopes in the neural code and to evaluate the effectiveness of stimulation strategies that aim to restore temporal processing across the auditory pathway with auditory prostheses.

Characterization of electrocorticographic, electromyographic and electrocardiographic recordings after the use of caffeine in Wistar rats

Objective:

To describe electrocorticographic, electromyographic and electrocardiographic profiles to report the electrophysiological effects of caffeine in Wistar rats.

Methods:

Male adult Wistar rats weighing 230g to 250g were used. Rats were allocated to one of two groups, as follows: Group 1, Control, intraperitoneal injection of 0.9% saline solution (n=27); and Group 2, treated with intraperitoneal injection of caffeine (50mg/kg; n=27). The rats were submitted to electrocorticographic, electromyographic and electrocardiographic assessment.

Results:

Brain oscillations (delta, theta, alpha, beta and gamma) in the frequency range up to 40Hz varied after caffeine administration to rats. Powers in delta and theta oscillations ranges were preponderant. The contractile force of the skeletal striated and cardiac muscles increased. Electrocardiogram analysis revealed shorter RR, QRS and QT intervals under the effect of caffeine.

Conclusion:

In the central nervous system, there was an increase in the delta, theta and alpha amplitude spectrum, which are related to memory encoding and enhanced learning. With regard to skeletal muscle, increased contraction of the gastrocnemius muscle was demonstrated, a clear indication of how caffeine can be used to enhance performance of some physical activities. Electrocardiographic changes observed after caffeine administration are primarily related to increased heart rate and energy consumption.

Delta- and theta-band cortical tracking and phase-amplitude coupling to sung speech by infants

The amplitude envelope of speech carries crucial low-frequency acoustic information that assists linguistic decoding at multiple time scales. Neurophysiological signals are known to track the amplitude envelope of adult-directed speech (ADS), particularly in the theta-band. Acoustic analysis of infant-directed speech (IDS) has revealed significantly greater modulation energy than ADS in an amplitude-modulation (AM) band centred on ∼2 Hz. Accordingly, cortical tracking of IDS by delta-band neural signals may be key to language acquisition. Speech also contains acoustic information within its higher-frequency bands (beta, gamma). Adult EEG and MEG studies reveal an oscillatory hierarchy, whereby low-frequency (delta, theta) neural phase dynamics temporally organize the amplitude of high-frequency signals (phase amplitude coupling, PAC). Whilst consensus is growing around the role of PAC in the matured adult brain, its role in the development of speech processing is unexplored. Here, we examined the presence and maturation of low-frequency (<12 Hz) cortical speech tracking in infants by recording EEG longitudinally from 60 participants when aged 4-, 7- and 11- months as they listened to nursery rhymes. After establishing stimulus-related neural signals in delta and theta, cortical tracking at each age was assessed in the delta, theta and alpha [control] bands using a multivariate temporal response function (mTRF) method. Delta-beta, delta-gamma, theta-beta and theta-gamma phase-amplitude coupling (PAC) was also assessed. Significant delta and theta but not alpha tracking was found. Significant PAC was present at all ages, with both delta and theta -driven coupling observed.

Effect of visual input on syllable parsing in a computational model of a neural microcircuit for speech processing

Objective.Seeing a person talking can help us understand them, particularly in a noisy environment. However, how the brain integrates the visual information with the auditory signal to enhance speech comprehension remains poorly understood.Approach.Here we address this question in a computational model of a cortical microcircuit for speech processing. The model consists of an excitatory and an inhibitory neural population that together create oscillations in the theta frequency range. When stimulated with speech, the theta rhythm becomes entrained to the onsets of syllables, such that the onsets can be inferred from the network activity. We investigate how well the obtained syllable parsing performs when different types of visual stimuli are added. In particular, we consider currents related to the rate of syllables as well as currents related to the mouth-opening area of the talking faces.Main results.We find that currents that target the excitatory neuronal population can influence speech comprehension, both boosting it or impeding it, depending on the temporal delay and on whether the currents are excitatory or inhibitory. In contrast, currents that act on the inhibitory neurons do not impact speech comprehension significantly.Significance.Our results suggest neural mechanisms for the integration of visual information with the acoustic information in speech and make experimentally-testable predictions.

Inaccurate cortical tracking of speech in adults with impaired speech perception in noise

Impaired speech perception in noise despite normal peripheral auditory function is a common problem in young adults. Despite a growing body of research, the pathophysiology of this impairment remains unknown. This magnetoencephalography study characterizes the cortical tracking of speech in a multi-talker background in a group of highly selected adult subjects with impaired speech perception in noise without peripheral auditory dysfunction. Magnetoencephalographic signals were recorded from 13 subjects with impaired speech perception in noise (six females, mean age: 30 years) and matched healthy subjects while they were listening to 5 different recordings of stories merged with a multi-talker background at different signal to noise ratios (No Noise, +10, +5, 0 and −5 dB). The cortical tracking of speech was quantified with coherence between magnetoencephalographic signals and the temporal envelope of (i) the global auditory scene (i.e. the attended speech stream and the multi-talker background noise), (ii) the attended speech stream only and (iii) the multi-talker background noise. Functional connectivity was then estimated between brain areas showing altered cortical tracking of speech in noise in subjects with impaired speech perception in noise and the rest of the brain. All participants demonstrated a selective cortical representation of the attended speech stream in noisy conditions, but subjects with impaired speech perception in noise displayed reduced cortical tracking of speech at the syllable rate (i.e. 4–8 Hz) in all noisy conditions. Increased functional connectivity was observed in subjects with impaired speech perception in noise in Noiseless and speech in noise conditions between supratemporal auditory cortices and left-dominant brain areas involved in semantic and attention processes. The difficulty to understand speech in a multi-talker background in subjects with impaired speech perception in noise appears to be related to an inaccurate auditory cortex tracking of speech at the syllable rate. The increased functional connectivity between supratemporal auditory cortices and language/attention-related neocortical areas probably aims at supporting speech perception and subsequent recognition in adverse auditory scenes. Overall, this study argues for a central origin of impaired speech perception in noise in the absence of any peripheral auditory dysfunction.

COSMO-Onset: A Neurally-Inspired Computational Model of Spoken Word Recognition, Combining Top-Down Prediction and Bottom-Up Detection of Syllabic Onsets

Recent neurocognitive models commonly consider speech perception as a hierarchy of processes, each corresponding to specific temporal scales of collective oscillatory processes in the cortex: 30-80 Hz gamma oscillations in charge of phonetic analysis, 4-9 Hz theta oscillations in charge of syllabic segmentation, 1-2 Hz delta oscillations processing prosodic/syntactic units and the 15-20 Hz beta channel possibly involved in top-down predictions. Several recent neuro-computational models thus feature theta oscillations, driven by the speech acoustic envelope, to achieve syllabic parsing before lexical access. However, it is unlikely that such syllabic parsing, performed in a purely bottom-up manner from envelope variations, would be totally efficient in all situations, especially in adverse sensory conditions. We present a new probabilistic model of spoken word recognition, called COSMO-Onset, in which syllabic parsing relies on fusion between top-down, lexical prediction of onset events and bottom-up onset detection from the acoustic envelope. We report preliminary simulations, analyzing how the model performs syllabic parsing and phone, syllable and word recognition. We show that, while purely bottom-up onset detection is sufficient for word recognition in nominal conditions, top-down prediction of syllabic onset events allows overcoming challenging adverse conditions, such as when the acoustic envelope is degraded, leading either to spurious or missing onset events in the sensory signal. This provides a proposal for a possible computational functional role of top-down, predictive processes during speech recognition, consistent with recent models of neuronal oscillatory processes.

One Way or Another: Cortical Language Areas Flexibly Adapt Processing Strategies to Perceptual And Contextual Properties of Speech

Cortical circuits rely on the temporal regularities of speech to optimize signal parsing for sound-to-meaning mapping. Bottom-up speech analysis is accelerated by top-down predictions about upcoming words. In everyday communications, however, listeners are regularly presented with challenging input-fluctuations of speech rate or semantic content. In this study, we asked how reducing speech temporal regularity affects its processing-parsing, phonological analysis, and ability to generate context-based predictions. To ensure that spoken sentences were natural and approximated semantic constraints of spontaneous speech we built a neural network to select stimuli from large corpora. We analyzed brain activity recorded with magnetoencephalography during sentence listening using evoked responses, speech-to-brain synchronization and representational similarity analysis. For normal speech theta band (6.5-8 Hz) speech-to-brain synchronization was increased and the left fronto-temporal areas generated stronger contextual predictions. The reverse was true for temporally irregular speech-weaker theta synchronization and reduced top-down effects. Interestingly, delta-band (0.5 Hz) speech tracking was greater when contextual/semantic predictions were lower or if speech was temporally jittered. We conclude that speech temporal regularity is relevant for (theta) syllabic tracking and robust semantic predictions while the joint support of temporal and contextual predictability reduces word and phrase-level cortical tracking (delta).

Cortical Tracking of a Background Speaker Modulates the Comprehension of a Foreground Speech Signal

Understanding speech in background noise is a difficult task. The tracking of speech rhythms such as the rate of syllables and words by cortical activity has emerged as a key neural mechanism for speech-in-noise comprehension. In particular, recent investigations have used transcranial alternating current stimulation (tACS) with the envelope of a speech signal to influence the cortical speech tracking, demonstrating that this type of stimulation modulates comprehension and therefore providing evidence of a functional role of the cortical tracking in speech processing. Cortical activity has been found to track the rhythms of a background speaker as well, but the functional significance of this neural response remains unclear. Here we use a speech-comprehension task with a target speaker in the presence of a distractor voice to show that tACS with the speech envelope of the target voice as well as tACS with the envelope of the distractor speaker both modulate the comprehension of the target speech. Because the envelope of the distractor speech does not carry information about the target speech stream, the modulation of speech comprehension through tACS with this envelope provides evidence that the cortical tracking of the background speaker affects the comprehension of the foreground speech signal. The phase dependency of the resulting modulation of speech comprehension is, however, opposite to that obtained from tACS with the envelope of the target speech signal. This suggests that the cortical tracking of the ignored speech stream and that of the attended speech stream may compete for neural resources.SIGNIFICANCE STATEMENT Loud environments such as busy pubs or restaurants can make conversation difficult. However, they also allow us to eavesdrop into other conversations that occur in the background. In particular, we often notice when somebody else mentions our name, even if we have not been listening to that person. However, the neural mechanisms by which background speech is processed remain poorly understood. Here we use transcranial alternating current stimulation, a technique through which neural activity in the cerebral cortex can be influenced, to show that cortical responses to rhythms in the distractor speech modulate the comprehension of the target speaker. Our results provide evidence that the cortical tracking of background speech rhythms plays a functional role in speech processing.

Transmission delays and frequency detuning can regulate information flow between brain regions

Brain networks exhibit very variable and dynamical functional connectivity and flexible configurations of information exchange despite their overall fixed structure. Brain oscillations are hypothesized to underlie time-dependent functional connectivity by periodically changing the excitability of neural populations. In this paper, we investigate the role of the connection delay and the detuning between the natural frequencies of neural populations in the transmission of signals. Based on numerical simulations and analytical arguments, we show that the amount of information transfer between two oscillating neural populations could be determined by their connection delay and the mismatch in their oscillation frequencies. Our results highlight the role of the collective phase response curve of the oscillating neural populations for the efficacy of signal transmission and the quality of the information transfer in brain networks.

Differential contributions of synaptic and intrinsic inhibitory currents to speech segmentation via flexible phase-locking in neural oscillators

Current hypotheses suggest that speech segmentation—the initial division and grouping of the speech stream into candidate phrases, syllables, and phonemes for further linguistic processing—is executed by a hierarchy of oscillators in auditory cortex. Theta (∼3-12 Hz) rhythms play a key role by phase-locking to recurring acoustic features marking syllable boundaries. Reliable synchronization to quasi-rhythmic inputs, whose variable frequency can dip below cortical theta frequencies (down to ∼1 Hz), requires “flexible” theta oscillators whose underlying neuronal mechanisms remain unknown. Using biophysical computational models, we found that the flexibility of phase-locking in neural oscillators depended on the types of hyperpolarizing currents that paced them. Simulated cortical theta oscillators flexibly phase-locked to slow inputs when these inputs caused both (i) spiking and (ii) the subsequent buildup of outward current sufficient to delay further spiking until the next input. The greatest flexibility in phase-locking arose from a synergistic interaction between intrinsic currents that was not replicated by synaptic currents at similar timescales. Flexibility in phase-locking enabled improved entrainment to speech input, optimal at mid-vocalic channels, which in turn supported syllabic-timescale segmentation through identification of vocalic nuclei. Our results suggest that synaptic and intrinsic inhibition contribute to frequency-restricted and -flexible phase-locking in neural oscillators, respectively. Their differential deployment may enable neural oscillators to play diverse roles, from reliable internal clocking to adaptive segmentation of quasi-regular sensory inputs like speech.

Oscillatory activity in auditory cortex is believed to play an important role in auditory and speech processing. One suggested function of these rhythms is to divide the speech stream into candidate phonemes, syllables, words, and phrases, to be matched with learned linguistic templates. This requires brain rhythms to flexibly synchronize with regular acoustic features of the speech stream. How neuronal circuits implement this task remains unknown. In this study, we explored the contribution of inhibitory currents to flexible phase-locking in neuronal theta oscillators, believed to perform initial syllabic segmentation. We found that a combination of specific intrinsic inhibitory currents at multiple timescales, present in a large class of cortical neurons, enabled exceptionally flexible phase-locking, which could be used to precisely segment speech by identifying vowels at mid-syllable. This suggests that the cells exhibiting these currents are a key component in the brain’s auditory and speech processing architecture.

Statistical learning and prosodic bootstrapping differentially affect neural synchronization during speech segmentation

Neural oscillations constitute an intrinsic property of functional brain organization that facilitates the tracking of linguistic units at multiple time scales through brain-to-stimulus alignment. This ubiquitous neural principle has been shown to facilitate speech segmentation and word learning based on statistical regularities. However, there is no common agreement yet on whether speech segmentation is mediated by a transition of neural synchronization from syllable to word rate, or whether the two time scales are concurrently tracked. Furthermore, it is currently unknown whether syllable transition probability contributes to speech segmentation when lexical stress cues can be directly used to extract word forms. Using Inter-Trial Coherence (ITC) analyses in combinations with Event-Related Potentials (ERPs), we showed that speech segmentation based on both statistical regularities and lexical stress cues was accompanied by concurrent neural synchronization to syllables and words. In particular, ITC at the word rate was generally higher in structured compared to random sequences, and this effect was particularly pronounced in the flat condition. Furthermore, ITC at the syllable rate dynamically increased across the blocks of the flat condition, whereas a similar modulation was not observed in the stressed condition. Notably, in the flat condition ITC at both time scales correlated with each other, and changes in neural synchronization were accompanied by a rapid reconfiguration of the P200 and N400 components with a close relationship between ITC and ERPs. These results highlight distinct computational principles governing neural synchronization to pertinent linguistic units while segmenting speech under different listening conditions.

Speech-brain phase coupling is enhanced in low contextual semantic predictability conditions

Semantic prediction and cortical entrainment to the acoustic landmarks of the speech envelope are two fundamental yet qualitatively different mechanisms that facilitate speech comprehension. However, it is not clear how and to what extent those mechanisms interact with each other. On the one hand, richer semantic context could enhance the perceptual representation of a predictable stimulus, thus improving speech entrainment. On the other hand, pre-activating an upcoming item could inhibit further bottom-up analyses to minimize processing costs, thus weakening speech entrainment. To test these competing hypotheses, we recorded EEG activity from 27 participants while they listened to a 14-min recording of text reading. The passage contained target words presented twice: once in a highly constraining and once in a minimally constraining context. First, we measured event related potentials on target words in the two conditions. In line with previous research, we showed that semantic predictability modulated the N400 amplitude: words in minimally constraining contexts elicited larger negative amplitudes than words in highly constraining contexts between 250 and 450 ms. Second, we evaluated speech entrainment effects by analyzing phase alignment between neural activity and the envelope of target words. Importantly, we found increased speech entrainment for words in minimally constraining compared to highly constraining contexts between 400 and 450 ms. Both effects were located in central electrodes and were significantly correlated. Our results indicate a trade-off between semantic pre-activation and cortical entrainment to speech and support the cost minimization hypothesis.

Speech categorization is better described by induced rather than evoked neural activity

Categorical perception (CP) describes how the human brain categorizes speech despite inherent acoustic variability. We examined neural correlates of CP in both evoked and induced electroencephalogram (EEG) activity to evaluate which mode best describes the process of speech categorization. Listeners labeled sounds from a vowel gradient while we recorded their EEGs. Using a source reconstructed EEG, we used band-specific evoked and induced neural activity to build parameter optimized support vector machine models to assess how well listeners' speech categorization could be decoded via whole-brain and hemisphere-specific responses. We found whole-brain evoked β-band activity decoded prototypical from ambiguous speech sounds with ∼70% accuracy. However, induced γ-band oscillations showed better decoding of speech categories with ∼95% accuracy compared to evoked β-band activity (∼70% accuracy). Induced high frequency (γ-band) oscillations dominated CP decoding in the left hemisphere, whereas lower frequencies (θ-band) dominated the decoding in the right hemisphere. Moreover, feature selection identified 14 brain regions carrying induced activity and 22 regions of evoked activity that were most salient in describing category-level speech representations. Among the areas and neural regimes explored, induced γ-band modulations were most strongly associated with listeners' behavioral CP. The data suggest that the category-level organization of speech is dominated by relatively high frequency induced brain rhythms.

Delta/Theta band EEG activity shapes the rhythmic perceptual sampling of auditory scenes

Many studies speak in favor of a rhythmic mode of listening, by which the encoding of acoustic information is structured by rhythmic neural processes at the time scale of about 1 to 4 Hz. Indeed, psychophysical data suggest that humans sample acoustic information in extended soundscapes not uniformly, but weigh the evidence at different moments for their perceptual decision at the time scale of about 2 Hz. We here test the critical prediction that such rhythmic perceptual sampling is directly related to the state of ongoing brain activity prior to the stimulus. Human participants judged the direction of frequency sweeps in 1.2 s long soundscapes while their EEG was recorded. We computed the perceptual weights attributed to different epochs within these soundscapes contingent on the phase or power of pre-stimulus EEG activity. This revealed a direct link between 4 Hz EEG phase and power prior to the stimulus and the phase of the rhythmic component of these perceptual weights. Hence, the temporal pattern by which the acoustic information is sampled over time for behavior is directly related to pre-stimulus brain activity in the delta/theta band. These results close a gap in the mechanistic picture linking ongoing delta band activity with their role in shaping the segmentation and perceptual influence of subsequent acoustic information.

EEG, MEG and neuromodulatory approaches to explore cognition: Current status and future directions

Neural oscillations and their association with brain states and cognitive functions have been object of extensive investigation over the last decades. Several electroencephalography (EEG) and magnetoencephalography (MEG) analysis approaches have been explored and oscillatory properties have been identified, in parallel with the technical and computational advancement. This review provides an up-to-date account of how EEG/MEG oscillations have contributed to the understanding of cognition. Methodological challenges, recent developments and translational potential, along with future research avenues, are discussed.

Stimulus-evoked phase-locked activity along the human auditory pathway strongly varies across individuals

Phase-locking to the temporal envelope of speech is associated with envelope processing and speech perception. The phase-locked activity of the auditory pathway, across modulation frequencies, is generally assessed at group level and shows a decrease in response magnitude with increasing modulation frequency. With the exception of increased activity around 40 and 80 to 100 Hz. Furthermore, little is known about the phase-locked response patterns to modulation frequencies ≤ 20 Hz, which are modulations predominately present in the speech envelope. In the present study we assess the temporal modulation transfer function (TMTF_ASSR) of the phase-locked activity of the auditory pathway, from 0.5 to 100 Hz at a high-resolution and by means of auditory steady-state responses. Although the group-averaged TMTF_ASSR corresponds well with those reported in the literature, the individual TMTF_ASSR shows a remarkable intersubject variability. This intersubject variability is especially present for ASSRs that originate from the cortex and are evoked with modulation frequencies ≤ 20 Hz. Moreover, we found that these cortical phase-locked activity patterns are robust over time. These results show the importance of the individual TMTF_ASSR when assessing phase-locked activity to envelope fluctuations, which can potentially be used as a marker for auditory processing.

The role of isochrony in speech perception in noise

The role of isochrony in speech—the hypothetical division of speech units into equal duration intervals—has been the subject of a long-standing debate. Current approaches in neurosciences have brought new perspectives in that debate through the theoretical framework of predictive coding and cortical oscillations. Here we assess the comparative roles of naturalness and isochrony in the intelligibility of speech in noise for French and English, two languages representative of two well-established contrastive rhythm classes. We show that both top-down predictions associated with the natural timing of speech and to a lesser extent bottom-up predictions associated with isochrony at a syllabic timescale improve intelligibility. We found a similar pattern of results for both languages, suggesting that temporal characterisation of speech from different rhythm classes could be unified around a single core speech unit, with neurophysiologically defined duration and linguistically anchored temporal location. Taken together, our results suggest that isochrony does not seem to be a main dimension of speech processing, but may be a consequence of neurobiological processing constraints, manifesting in behavioural performance and ultimately explaining why isochronous stimuli occupy a particular status in speech and human perception in general.

Observation and assessment of acoustic contamination of electrophysiological brain signals during speech production and sound perception

OBJECTIVE

A current challenge of neurotechnologies is to develop speech brain-computer interfaces aiming at restoring communication in people unable to speak. To achieve a proof of concept of such system, neural activity of patients implanted for clinical reasons can be recorded while they speak. Using such simultaneously recorded audio and neural data, decoders can be built to predict speech features using features extracted from brain signals. A typical neural feature is the spectral power of field potentials in the high-gamma frequency band, which happens to overlap the frequency range of speech acoustic signals, especially the fundamental frequency of the voice. Here, we analyzed human electrocorticographic and intracortical recordings during speech production and perception as well as a rat microelectrocorticographic recording during sound perception. We observed that several datasets, recorded with different recording setups, contained spectrotemporal features highly correlated with those of the sound produced by or delivered to the participants, especially within the high-gamma band and above, strongly suggesting a contamination of electrophysiological recordings by the sound signal. This study investigated the presence of acoustic contamination and its possible source.

APPROACH

We developed analysis methods and a statistical criterion to objectively assess the presence or absence of contamination-specific correlations, which we used to screen several datasets from five centers worldwide.

MAIN RESULTS

Not all but several datasets, recorded in a variety of conditions, showed significant evidence of acoustic contamination. Three out of five centers were concerned by the phenomenon. In a recording showing high contamination, the use of high-gamma band features dramatically facilitated the performance of linear decoding of acoustic speech features, while such improvement was very limited for another recording showing no significant contamination. Further analysis and in vitro replication suggest that the contamination is caused by the mechanical action of the sound waves onto the cables and connectors along the recording chain, transforming sound vibrations into an undesired electrical noise affecting the biopotential measurements.

SIGNIFICANCE

Although this study does not per se question the presence of speech-relevant physiological information in the high-gamma range and above (multiunit activity), it alerts on the fact that acoustic contamination of neural signals should be proofed and eliminated before investigating the cortical dynamics of these processes. To this end, we make available a toolbox implementing the proposed statistical approach to quickly assess the extent of contamination in an electrophysiological recording (https://doi.org/10.5281/zenodo.3929296).

Modelling the effects of transcranial alternating current stimulation on the neural encoding of speech in noise

Transcranial alternating current stimulation (tACS) can non-invasively modulate neuronal activity in the cerebral cortex, in particular at the frequency of the applied stimulation. Such modulation can matter for speech processing, since the latter involves the tracking of slow amplitude fluctuations in speech by cortical activity. tACS with a current signal that follows the envelope of a speech stimulus has indeed been found to influence the cortical tracking and to modulate the comprehension of the speech in background noise. However, how exactly tACS influences the speech-related cortical activity, and how it causes the observed effects on speech comprehension, remains poorly understood. A computational model for cortical speech processing in a biophysically plausible spiking neural network has recently been proposed. Here we extended the model to investigate the effects of different types of stimulation waveforms, similar to those previously applied in experimental studies, on the processing of speech in noise. We assessed in particular how well speech could be decoded from the neural network activity when paired with the exogenous stimulation. We found that, in the absence of current stimulation, the speech-in-noise decoding accuracy was comparable to the comprehension of speech in background noise of human listeners. We further found that current stimulation could alter the speech decoding accuracy by a few percent, comparable to the effects of tACS on speech-in-noise comprehension. Our simulations further allowed us to identify the parameters for the stimulation waveforms that yielded the largest enhancement of speech-in-noise encoding. Our model thereby provides insight into the potential neural mechanisms by which weak alternating current stimulation may influence speech comprehension and allows to screen a large range of stimulation waveforms for their effect on speech processing.

Phase-amplitude coupling profiles differ in frontal and auditory cortices of bats

Neural oscillations are at the core of important computations in the mammalian brain. Interactions between oscillatory activities in different frequency bands, such as delta (1-4 Hz), theta (4-8 Hz) or gamma (>30 Hz), are a powerful mechanism for binding fundamentally distinct spatiotemporal scales of neural processing. Phase-amplitude coupling (PAC) is one such plausible and well-described interaction, but much is yet to be uncovered regarding how PAC dynamics contribute to sensory representations. In particular, although PAC appears to have a major role in audition, the characteristics of coupling profiles in sensory and integration (i.e. frontal) cortical areas remain obscure. Here, we address this question by studying PAC dynamics in the frontal-auditory field (FAF; an auditory area in the bat frontal cortex) and the auditory cortex (AC) of the bat Carollia perspicillata. By means of simultaneous electrophysiological recordings in frontal and auditory cortices examining local-field potentials (LFPs), we show that the amplitude of gamma-band activity couples with the phase of low-frequency LFPs in both structures. Our results demonstrate that the coupling in FAF occurs most prominently in delta/high-gamma frequencies (1-4/75-100 Hz), whereas in the AC the coupling is strongest in the delta-theta/low-gamma (2-8/25-55 Hz) range. We argue that distinct PAC profiles may represent different mechanisms for neuronal processing in frontal and auditory cortices, and might complement oscillatory interactions for sensory processing in the frontal-auditory cortex network.

A Temporal Sampling Basis for Visual Processing in Developmental Dyslexia

Knowledge of oscillatory entrainment and its fundamental role in cognitive and behavioral processing has increasingly been applied to research in the field of reading and developmental dyslexia. Growing evidence indicates that oscillatory entrainment to theta frequency spoken language in the auditory domain, along with cross-frequency theta-gamma coupling, support phonological processing (i.e., cognitive encoding of linguistic knowledge gathered from speech) which is required for reading. This theory is called the temporal sampling framework (TSF) and can extend to developmental dyslexia, such that inadequate temporal sampling of speech-sounds in people with dyslexia results in poor theta oscillatory entrainment in the auditory domain, and thus a phonological processing deficit which hinders reading ability. We suggest that inadequate theta oscillations in the visual domain might account for the many magno-dorsal processing, oculomotor control and visual deficits seen in developmental dyslexia. We propose two possible models of a magno-dorsal visual correlate to the auditory TSF: (1) A direct correlate that involves "bottom-up" magnocellular oscillatory entrainment of the visual domain that occurs when magnocellular populations phase lock to theta frequency fixations during reading and (2) an inverse correlate whereby attending to text triggers "top-down" low gamma signals from higher-order visual processing areas, thereby organizing magnocellular populations to synchronize to a theta frequency to drive the temporal control of oculomotor movements and capturing of letter images at a higher frequency.

Combining predictive coding and neural oscillations enables online syllable recognition in natural speech

On-line comprehension of natural speech requires segmenting the acoustic stream into discrete linguistic elements. This process is argued to rely on theta-gamma oscillation coupling, which can parse syllables and encode them in decipherable neural activity. Speech comprehension also strongly depends on contextual cues that help predicting speech structure and content. To explore the effects of theta-gamma coupling on bottom-up/top-down dynamics during on-line syllable identification, we designed a computational model (Precoss—predictive coding and oscillations for speech) that can recognise syllable sequences in continuous speech. The model uses predictions from internal spectro-temporal representations of syllables and theta oscillations to signal syllable onsets and duration. Syllable recognition is best when theta-gamma coupling is used to temporally align spectro-temporal predictions with the acoustic input. This neurocomputational modelling work demonstrates that the notions of predictive coding and neural oscillations can be brought together to account for on-line dynamic sensory processing.

The authors present a model to parse and recognise syllables on-line in natural speech sentences that combine predictive coding and neural oscillations. They use simulations from different versions of the model to establish the importance of both theta-gamma coupling and the reset of accumulated evidence in continuous speech processing.

Early Interactive Acoustic Experience with Non-speech Generalizes to Speech and Confers a Syllabic Processing Advantage at 9 Months

During early development, the infant brain is highly plastic and sensory experiences modulate emerging cortical maps, enhancing processing efficiency as infants set up key linguistic precursors. Early interactive acoustic experience (IAE) with spectrotemporally-modulated non-speech has been shown to facilitate optimal acoustic processing and generalizes to novel non-speech sounds at 7-months-of-age. Here we demonstrate that effects of non-speech IAE endure well beyond the immediate training period and robustly generalize to speech processing. Infants who received non-speech IAE differed at 9-months-of-age from both naïve controls and those with only passive acoustic exposure, demonstrating broad modulation of oscillatory dynamics. For the standard syllable, increased high-gamma (>70 Hz) power within auditory cortices indicates that IAE fosters native speech processing, facilitating establishment of phonemic representations. The higher left beta power seen may reflect increased linking of sensory information and corresponding articulatory patterns, while bilateral decreases in theta power suggest more mature automatized speech processing, as less neuronal resources were allocated to process syllabic information. For the deviant syllable, left-lateralized gamma (<70 Hz) enhancement suggests IAE promotes phonemic-related discrimination abilities. Theta power increases in right auditory cortex, known for favoring slow-rate decoding, implies IAE facilitates the more demanding processing of the sporadic deviant syllable.

Converging intracortical signatures of two separated processing timescales in human early auditory cortex

Neural oscillations in auditory cortex are argued to support parsing and representing speech constituents at their corresponding temporal scales. Yet, how incoming sensory information interacts with ongoing spontaneous brain activity, what features of the neuronal microcircuitry underlie spontaneous and stimulus-evoked spectral fingerprints, and what these fingerprints entail for stimulus encoding, remain largely open questions. We used a combination of human invasive electrophysiology, computational modeling and decoding techniques to assess the information encoding properties of brain activity and to relate them to a plausible underlying neuronal microarchitecture. We analyzed intracortical auditory EEG activity from 10 patients while they were listening to short sentences. Pre-stimulus neural activity in early auditory cortical regions often exhibited power spectra with a shoulder in the delta range and a small bump in the beta range. Speech decreased power in the beta range, and increased power in the delta-theta and gamma ranges. Using multivariate machine learning techniques, we assessed the spectral profile of information content for two aspects of speech processing: detection and discrimination. We obtained better phase than power information decoding, and a bimodal spectral profile of information content with better decoding at low (delta-theta) and high (gamma) frequencies than at intermediate (beta) frequencies. These experimental data were reproduced by a simple rate model made of two subnetworks with different timescales, each composed of coupled excitatory and inhibitory units, and connected via a negative feedback loop. Modeling and experimental results were similar in terms of pre-stimulus spectral profile (except for the iEEG beta bump), spectral modulations with speech, and spectral profile of information content. Altogether, we provide converging evidence from both univariate spectral analysis and decoding approaches for a dual timescale processing infrastructure in human auditory cortex, and show that it is consistent with the dynamics of a simple rate model.

Genuine cross-frequency coupling networks in human resting-state electrophysiological recordings

Phase synchronization of neuronal oscillations in specific frequency bands coordinates anatomically distributed neuronal processing and communication. Typically, oscillations and synchronization take place concurrently in many distinct frequencies, which serve separate computational roles in cognitive functions. While within-frequency phase synchronization has been studied extensively, less is known about the mechanisms that govern neuronal processing distributed across frequencies and brain regions. Such integration of processing between frequencies could be achieved via cross-frequency coupling (CFC), either by phase–amplitude coupling (PAC) or by n:m-cross–frequency phase synchrony (CFS). So far, studies have mostly focused on local CFC in individual brain regions, whereas the presence and functional organization of CFC between brain areas have remained largely unknown. We posit that interareal CFC may be essential for large-scale coordination of neuronal activity and investigate here whether genuine CFC networks are present in human resting-state (RS) brain activity. To assess the functional organization of CFC networks, we identified brain-wide CFC networks at mesoscale resolution from stereoelectroencephalography (SEEG) and at macroscale resolution from source-reconstructed magnetoencephalography (MEG) data. We developed a novel, to our knowledge, graph-theoretical method to distinguish genuine CFC from spurious CFC that may arise from nonsinusoidal signals ubiquitous in neuronal activity. We show that genuine interareal CFC is present in human RS activity in both SEEG and MEG data. Both CFS and PAC networks coupled theta and alpha oscillations with higher frequencies in large-scale networks connecting anterior and posterior brain regions. CFS and PAC networks had distinct spectral patterns and opposing distribution of low- and high-frequency network hubs, implying that they constitute distinct CFC mechanisms. The strength of CFS networks was also predictive of cognitive performance in a separate neuropsychological assessment. In conclusion, these results provide evidence for interareal CFS and PAC being 2 distinct mechanisms for coupling oscillations across frequencies in large-scale brain networks.

Genuine interareal cross-frequency coupling (CFC) can be identified from human resting state activity using magnetoencephalography, stereoelectroencephalography, and novel network approaches. CFC couples slow theta and alpha oscillations to faster oscillations across brain regions.

Oscillations in the auditory system and their possible role

GOURÉVITCH, B., C. Martin, O. Postal, J.J. Eggermont. Oscillations in the auditory system, their possible role. NEUROSCI BIOBEHAV REV XXX XXX-XXX, 2020. - Neural oscillations are thought to have various roles in brain processing such as, attention modulation, neuronal communication, motor coordination, memory consolidation, decision-making, or feature binding. The role of oscillations in the auditory system is less clear, especially due to the large discrepancy between human and animal studies. Here we describe many methodological issues that confound the results of oscillation studies in the auditory field. Moreover, we discuss the relationship between neural entrainment and oscillations that remains unclear. Finally, we aim to identify which kind of oscillations could be specific or salient to the auditory areas and their processing. We suggest that the role of oscillations might dramatically differ between the primary auditory cortex and the more associative auditory areas. Despite the moderate presence of intrinsic low frequency oscillations in the primary auditory cortex, rhythmic components in the input seem crucial for auditory processing. This allows the phase entrainment between the oscillatory phase and rhythmic input, which is an integral part of stimulus selection within the auditory system.