Power and phase coherence in sensorimotor mu and temporal lobe alpha components during covert and overt syllable production

Reduced resting-state periodic beta power in adults who stutter is related to sensorimotor control of speech execution

OBJECTIVE

The primary aim of the current study was to determine whether adults who stutter (AWS) present with anomalous periodic beta (β) rhythms when compared to typically fluent adults in the eyes-open resting state. A second aim was to determine whether lower β power in the RS is related to a measure of β event-related desynchronization (ERD) during syllable sequence execution.

METHODS

EEG data was collected from 128 channels in a 5 min, eyes-open resting state condition and from a syllable sequence repetition task. Temporal independent component analysis (ICA) was used to separate volume conducted EEG sources and to find a set of component weights common to the RS and syllable repetition task. Both traditional measures of power spectral density (PSD) and parameterized spectra were computed for components showing peaks in the β band (13-30 Hz). Parameterization was used to evaluate separable components adjusted for the 1/f part of the spectrum.

RESULTS

ICA revealed frontal-parietal midline and lateral sensorimotor (μ) components common to the RS and a syllable repetition task with peaks in the β band. The entire spectrum for each component was modeled using the FOOOF algorithm. Independent samples t-tests revealed significantly lower periodic β in midline central-parietal and lateral sensorimotor components in AWS. Regression analysis suggested a significant relationship between left periodic sensorimotor β power in the RS and ERD during syllable sequence execution.

CONCLUSIONS

Findings suggest that periodic β peaks in the spectrum are related to hypothesized underlying pathophysiological differences in stuttering, including midline rhythms associated the default mode network (DMN) and lateral sensorimotor rhythms associated with the control of movement.

Functional Roles of Sensorimotor Alpha and Beta Oscillations in Overt Speech Production

Power decreases, or desynchronization, of sensorimotor alpha and beta oscillations (i.e., alpha and beta ERD) have long been considered as indices of sensorimotor control in overt speech production. However, their specific functional roles are not well understood. Hence, we first conducted a systematic review to investigate how these two oscillations are modulated by speech motor tasks in typically fluent speakers (TFS) and in persons who stutter (PWS). Eleven EEG/MEG papers with source localization were included in our systematic review. The results revealed consistent alpha and beta ERD in the sensorimotor cortex of TFS and PWS. Furthermore, the results suggested that sensorimotor alpha and beta ERD may be functionally dissociable, with alpha related to (somato-)sensory feedback processing during articulation and beta related to motor processes throughout planning and articulation. To (partly) test this hypothesis of a potential functional dissociation between alpha and beta ERD, we then analyzed existing intracranial electro-encephalography (iEEG) data from the primary somatosensory cortex (S1) of picture naming. We found moderate evidence for alpha, but not beta, ERD's sensitivity to speech movements in S1, lending supporting evidence for the functional dissociation hypothesis identified by the systematic review.

Source Localization and Spectrum Analyzing of EEG in Stuttering State upon Dysfluent Utterances

Purpose: The present study which addressed adults who stutter (AWS) attempted to investigate power spectral dynamics in the stuttering state by answering the questions using quantitative electroencephalography (qEEG). Method: A 64-channel electroencephalography (EEG) setup was used for data acquisition at 20 AWS. Since the speech, especially stuttering, causes significant noise in the EEG, 2 conditions of speech preparation (SP) and imagined speech (IS) were considered. EEG signals were decomposed into 6 bands. The corresponding sources were localized using the standard low-resolution electromagnetic tomography (sLORETA) tool in both fluent and dysfluent states. Results: Significant differences were noted after analyzing the time-locked EEG signals in fluent and dysfluent utterances. Consistent with previous studies, poor alpha and beta suppression in SP and IS conditions were localized in the left frontotemporal areas in a dysfluent state. This was partly true for the right frontal regions. In the theta range, disfluency was concurrence with increased activation in the left and right motor areas. Increased delta power in the left and right motor areas as well as increased beta2 power over left parietal regions was notable EEG features upon fluent speech. Conclusion: Based on the present findings and those of earlier studies, explaining the neural circuitries involved in stuttering probably requires an examination of the entire frequency spectrum involved in speech.

Finding tau rhythms in EEG: An independent component analysis approach

Tau rhythms are largely defined by sound responsive alpha band (~8-13 Hz) oscillations generated largely within auditory areas of the superior temporal gyri. Studies of tau have mostly employed magnetoencephalography or intracranial recording because of tau's elusiveness in the electroencephalogram. Here, we demonstrate that independent component analysis (ICA) decomposition can be an effective way to identify tau sources and study tau source activities in EEG recordings. Subjects (N = 18) were passively exposed to complex acoustic stimuli while the EEG was recorded from 68 electrodes across the scalp. Subjects' data were split into 60 parallel processing pipelines entailing use of five levels of high-pass filtering (passbands of 0.1, 0.5, 1, 2, and 4 Hz), three levels of low-pass filtering (25, 50, and 100 Hz), and four different ICA algorithms (fastICA, infomax, adaptive mixture ICA [AMICA], and multi-model AMICA [mAMICA]). Tau-related independent component (IC) processes were identified from this data as being localized near the superior temporal gyri with a spectral peak in the 8-13 Hz alpha band. These "tau ICs" showed alpha suppression during sound presentations that was not seen for other commonly observed IC clusters with spectral peaks in the alpha range (e.g., those associated with somatomotor mu, and parietal or occipital alpha). The choice of analysis parameters impacted the likelihood of obtaining tau ICs from an ICA decomposition. Lower cutoff frequencies for high-pass filtering resulted in significantly fewer subjects showing a tau IC than more aggressive high-pass filtering. Decomposition using the fastICA algorithm performed the poorest in this regard, while mAMICA performed best. The best combination of filters and ICA model choice was able to identify at least one tau IC in the data of ~94% of the sample. Altogether, the data reveal close similarities between tau EEG IC dynamics and tau dynamics observed in MEG and intracranial data. Use of relatively aggressive high-pass filters and mAMICA decomposition should allow researchers to identify and characterize tau rhythms in a majority of their subjects. We believe adopting the ICA decomposition approach to EEG analysis can increase the rate and range of discoveries related to auditory responsive tau rhythms.

Aberrant neurophysiological signaling associated with speech impairments in Parkinson's disease

Difficulty producing intelligible speech is a debilitating symptom of Parkinson's disease (PD). Yet, both the robust evaluation of speech impairments and the identification of the affected brain systems are challenging. Using task-free magnetoencephalography, we examine the spectral and spatial definitions of the functional neuropathology underlying reduced speech quality in patients with PD using a new approach to characterize speech impairments and a novel brain-imaging marker. We found that the interactive scoring of speech impairments in PD (N = 59) is reliable across non-expert raters, and better related to the hallmark motor and cognitive impairments of PD than automatically-extracted acoustical features. By relating these speech impairment ratings to neurophysiological deviations from healthy adults (N = 65), we show that articulation impairments in patients with PD are associated with aberrant activity in the left inferior frontal cortex, and that functional connectivity of this region with somatomotor cortices mediates the influence of cognitive decline on speech deficits.

Dynamic auditory contributions to error detection revealed in the discrimination of Same and Different syllable pairs

During speech production auditory regions operate in concert with the anterior dorsal stream to facilitate online error detection. As the dorsal stream also is known to activate in speech perception, the purpose of the current study was to probe the role of auditory regions in error detection during auditory discrimination tasks as stimuli are encoded and maintained in working memory. A priori assumptions are that sensory mismatch (i.e., error) occurs during the discrimination of Different (mismatched) but not Same (matched) syllable pairs. Independent component analysis was applied to raw EEG data recorded from 42 participants to identify bilateral auditory alpha rhythms, which were decomposed across time and frequency to reveal robust patterns of event related synchronization (ERS; inhibition) and desynchronization (ERD; processing) over the time course of discrimination events. Results were characterized by bilateral peri-stimulus alpha ERD transitioning to alpha ERS in the late trial epoch, with ERD interpreted as evidence of working memory encoding via Analysis by Synthesis and ERS considered evidence of speech-induced-suppression arising during covert articulatory rehearsal to facilitate working memory maintenance. The transition from ERD to ERS occurred later in the left hemisphere in Different trials than in Same trials, with ERD and ERS temporally overlapping during the early post-stimulus window. Results were interpreted to suggest that the sensory mismatch (i.e., error) arising from the comparison of the first and second syllable elicits further processing in the left hemisphere to support working memory encoding and maintenance. Results are consistent with auditory contributions to error detection during both encoding and maintenance stages of working memory, with encoding stage error detection associated with stimulus concordance and maintenance stage error detection associated with task-specific retention demands.

Green tea consumption and the management of adrenal stress hormones in adolescents who stutter

Green tea and its polyphenolic compounds have been shown to exert positive effects in individuals with psychological disorders. The protective role of green tea against stuttering or its related consequences, depression, anxiety and stress, were evaluated in adolescents with moderate stuttering (MS). A total of 60 adolescents aged (12-18) years old were enrolled in this study. Patients were classified according to standardized test material Stuttering Severity Instrument, 4th Edition was used to estimate the severity of stuttering; participants were classified into two groups: a normal healthy group (n=30) and a MS group (n=30). The Depression Anxiety Stress Scale and General Health Questionnaire were used to estimate the degree of depression, anxiety and stress as well as general mental health. The physiological profile of stress hormones, as a measure of the response to green tea response, was also measured amongst participants. Adrenal stress hormones cortisol, dehydroepiandrosterone (DHEA), acetylcholine (ACTH), corticosterone and the cortisol:DHEA ratio were assayed. In addition, the constituent green tea polyphenols and their quantities were determined using liquid chromatography analysis. Decaffeinated green tea was administered six cups/day for 6 weeks, and this significantly improved the depression, anxiety, stress and mental health consequences associated with stuttering in adolescents. In addition, increased consumption of green tea significantly reduced elevated levels of adrenal stress hormones; cortisol, DHEA, ACTH and corticosterone, and increased the cortisol:DHEA ratio in the control and adolescents who stuttered. The data showed that drinking six cups of decaffeinated green tea, which is enriched in catechins (1,580 mg) and other related polyphenols, was sufficient to improve the consequences of mental health associated with stuttering in younger aged individuals.

Imagined speech can be decoded from low- and cross-frequency intracranial EEG features

Reconstructing intended speech from neural activity using brain-computer interfaces holds great promises for people with severe speech production deficits. While decoding overt speech has progressed, decoding imagined speech has met limited success, mainly because the associated neural signals are weak and variable compared to overt speech, hence difficult to decode by learning algorithms. We obtained three electrocorticography datasets from 13 patients, with electrodes implanted for epilepsy evaluation, who performed overt and imagined speech production tasks. Based on recent theories of speech neural processing, we extracted consistent and specific neural features usable for future brain computer interfaces, and assessed their performance to discriminate speech items in articulatory, phonetic, and vocalic representation spaces. While high-frequency activity provided the best signal for overt speech, both low- and higher-frequency power and local cross-frequency contributed to imagined speech decoding, in particular in phonetic and vocalic, i.e. perceptual, spaces. These findings show that low-frequency power and cross-frequency dynamics contain key information for imagined speech decoding.

Audiovisual incongruence differentially impacts left and right hemisphere sensorimotor oscillations: Potential applications to production

Speech production gives rise to distinct auditory and somatosensory feedback signals which are dynamically integrated to enable online monitoring and error correction, though it remains unclear how the sensorimotor system supports the integration of these multimodal signals. Capitalizing on the parity of sensorimotor processes supporting perception and production, the current study employed the McGurk paradigm to induce multimodal sensory congruence/incongruence. EEG data from a cohort of 39 typical speakers were decomposed with independent component analysis to identify bilateral mu rhythms; indices of sensorimotor activity. Subsequent time-frequency analyses revealed bilateral patterns of event related desynchronization (ERD) across alpha and beta frequency ranges over the time course of perceptual events. Right mu activity was characterized by reduced ERD during all cases of audiovisual incongruence, while left mu activity was attenuated and protracted in McGurk trials eliciting sensory fusion. Results were interpreted to suggest distinct hemispheric contributions, with right hemisphere mu activity supporting a coarse incongruence detection process and left hemisphere mu activity reflecting a more granular level of analysis including phonological identification and incongruence resolution. Findings are also considered in regard to incongruence detection and resolution processes during production.

Sensorimotor contributions to working memory differ between the discrimination of Same and Different syllable pairs

Sensorimotor activity during speech perception is both pervasive and highly variable, changing as a function of the cognitive demands imposed by the task. The purpose of the current study was to evaluate whether the discrimination of Same (matched) and Different (unmatched) syllable pairs elicit different patterns of sensorimotor activity as stimuli are processed in working memory. Raw EEG data recorded from 42 participants were decomposed with independent component analysis to identify bilateral sensorimotor mu rhythms from 36 subjects. Time frequency decomposition of mu rhythms revealed concurrent event related desynchronization (ERD) in alpha and beta frequency bands across the peri- and post-stimulus time periods, which were interpreted as evidence of sensorimotor contributions to working memory encoding and maintenance. Left hemisphere alpha/beta ERD was stronger in Different trials than Same trials during the post-stimulus period, while right hemisphere alpha/beta ERD was stronger in Same trials than Different trials. A between-hemispheres contrast revealed no differences during Same trials, while post-stimulus alpha/beta ERD was stronger in the left hemisphere than the right during Different trials. Results were interpreted to suggest that predictive coding mechanisms lead to repetition suppression effects in Same trials. Mismatches arising from predictive coding mechanisms in Different trials shift subsequent working memory processing to the speech-dominant left hemisphere. Findings clarify how sensorimotor activity differentially supports working memory encoding and maintenance stages during speech discrimination tasks and have potential to inform sensorimotor models of speech perception and working memory.

Involvement of the Cortico-Basal Ganglia-Thalamocortical Loop in Developmental Stuttering

Stuttering is a complex neurodevelopmental disorder that has to date eluded a clear explication of its pathophysiological bases. In this review, we utilize the Directions Into Velocities of Articulators (DIVA) neurocomputational modeling framework to mechanistically interpret relevant findings from the behavioral and neurological literatures on stuttering. Within this theoretical framework, we propose that the primary impairment underlying stuttering behavior is malfunction in the cortico-basal ganglia-thalamocortical (hereafter, cortico-BG) loop that is responsible for initiating speech motor programs. This theoretical perspective predicts three possible loci of impaired neural processing within the cortico-BG loop that could lead to stuttering behaviors: impairment within the basal ganglia proper; impairment of axonal projections between cerebral cortex, basal ganglia, and thalamus; and impairment in cortical processing. These theoretical perspectives are presented in detail, followed by a review of empirical data that make reference to these three possibilities. We also highlight any differences that are present in the literature based on examining adults versus children, which give important insights into potential core deficits associated with stuttering versus compensatory changes that occur in the brain as a result of having stuttered for many years in the case of adults who stutter. We conclude with outstanding questions in the field and promising areas for future studies that have the potential to further advance mechanistic understanding of neural deficits underlying persistent developmental stuttering.

The Application of EEG Mu Rhythm Measures to Neurophysiological Research in Stuttering

Deficits in basal ganglia-based inhibitory and timing circuits along with sensorimotor internal modeling mechanisms are thought to underlie stuttering. However, much remains to be learned regarding the precise manner how these deficits contribute to disrupting both speech and cognitive functions in those who stutter. Herein, we examine the suitability of electroencephalographic (EEG) mu rhythms for addressing these deficits. We review some previous findings of mu rhythm activity differentiating stuttering from non-stuttering individuals and present some new preliminary findings capturing stuttering-related deficits in working memory. Mu rhythms are characterized by spectral peaks in alpha (8-13 Hz) and beta (14-25 Hz) frequency bands (mu-alpha and mu-beta). They emanate from premotor/motor regions and are influenced by basal ganglia and sensorimotor function. More specifically, alpha peaks (mu-alpha) are sensitive to basal ganglia-based inhibitory signals and sensory-to-motor feedback. Beta peaks (mu-beta) are sensitive to changes in timing and capture motor-to-sensory (i.e., forward model) projections. Observing simultaneous changes in mu-alpha and mu-beta across the time-course of specific events provides a rich window for observing neurophysiological deficits associated with stuttering in both speech and cognitive tasks and can provide a better understanding of the functional relationship between these stuttering symptoms. We review how independent component analysis (ICA) can extract mu rhythms from raw EEG signals in speech production tasks, such that changes in alpha and beta power are mapped to myogenic activity from articulators. We review findings from speech production and auditory discrimination tasks demonstrating that mu-alpha and mu-beta are highly sensitive to capturing sensorimotor and basal ganglia deficits associated with stuttering with high temporal precision. Novel findings from a non-word repetition (working memory) task are also included. They show reduced mu-alpha suppression in a stuttering group compared to a typically fluent group. Finally, we review current limitations and directions for future research.