Sensorimotor activity measured via oscillations of EEG mu rhythms in speech and non-speech discrimination tasks with and without segmentation demands

thebeat: A Python package for working with rhythms and other temporal sequences

thebeat is a Python package for working with temporal sequences and rhythms in the behavioral and cognitive sciences, as well as in bioacoustics. It provides functionality for creating experimental stimuli, and for visualizing and analyzing temporal data. Sequences, sounds, and experimental trials can be generated using single lines of code. thebeat contains functions for calculating common rhythmic measures, such as interval ratios, and for producing plots, such as circular histograms. thebeat saves researchers time when creating experiments, and provides the first steps in collecting widely accepted methods for use in timing research. thebeat is an open-source, on-going, and collaborative project, and can be extended for use in specialized subfields. thebeat integrates easily with the existing Python ecosystem, allowing one to combine our tested code with custom-made scripts. The package was specifically designed to be useful for both skilled and novice programmers. thebeat provides a foundation for working with temporal sequences onto which additional functionality can be built. This combination of specificity and plasticity should facilitate research in multiple research contexts and fields of study.

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.

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.

EEG power spectral dynamics associated with listening in adverse conditions

Adverse listening conditions increase the demand on cognitive resources needed for speech comprehension. In an exploratory study, we aimed to identify independent power spectral features in the EEG useful for studying the cognitive processes involved in this effortful listening. Listeners performed the coordinate response measure task with a single-talker masker at a 0-dB signal-to-noise ratio. Sounds were left unfiltered or degraded with low-pass filtering. Independent component analysis (ICA) was used to identify independent components (ICs) in the EEG data, the power spectral dynamics of which were then analyzed. Frontal midline theta, left frontal, right frontal, left mu, right mu, left temporal, parietal, left occipital, central occipital, and right occipital clusters of ICs were identified. All IC clusters showed some significant listening-related changes in their power spectrum. This included sustained theta enhancements, gamma enhancements, alpha enhancements, alpha suppression, beta enhancements, and mu rhythm suppression. Several of these effects were absent or negligible using traditional channel analyses. Comparison of filtered to unfiltered speech revealed a stronger alpha suppression in the parietal and central occipital clusters of ICs for the filtered speech condition. This not only replicates recent findings showing greater alpha suppression as listening difficulty increases but also suggests that such alpha-band effects can stem from multiple cortical sources. We lay out the advantages of the ICA approach over the restrictive analyses that have been used as of late in the study of listening effort. We also make suggestions for moving into hypothesis-driven studies regarding the power spectral features that were revealed.

Quantitative EEG measures in profoundly deaf and normal hearing individuals while performing a vibrotactile temporal discrimination task

Challenges in early oral language acquisition in profoundly deaf individuals have an impact on cognitive neurodevelopment. This has led to the exploration of alternative sound perception methods involving training of vibrotactile discrimination of sounds within the language spectrum. In particular, stimulus duration plays an important role in linguistic categorical perception. We comparatively evaluated vibrotactile temporal discrimination of sound and how specific training can modify the underlying electrical brain activity. Fifteen profoundly deaf (PD) and 15 normal-hearing (NH) subjects performed a vibrotactile oddball task with simultaneous EEG recording, before and after a short training period (5 one-hour sessions; in 2.5-3 weeks). The stimuli consisted of 700 Hz pure-tones with different duration (target: long 500 ms; non-target: short 250 ms). The sound-wave stimuli were delivered by a small device worn on the right index finger. A similar behavioral training effect was observed in both groups showing significant improvement in sound-duration discrimination. However, quantitative EEG measurements reveal distinct neurophysiological patterns characterized by higher and more diffuse delta band magnitudes in the PD group, together with a generalized decrement in absolute power in both groups that might reflect a facilitating process associated to learning. Furthermore, training-related changes were found in the beta-band in NH. Findings suggest PD have different cognitive adaptive mechanisms which are not a mere amplification effect due to greater cortical excitability.

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.

Sex differences in early sensorimotor processing for speech discrimination

Sensorimotor activity in speech perception tasks varies as a function of context, cognitive load, and cognitive ability. This study investigated listener sex as an additional variable. Raw EEG data were collected as 21 males and 21 females discriminated /ba/ and /da/ in quiet and noisy backgrounds. Independent component analyses of data from accurately discriminated trials identified sensorimotor mu components with characteristic alpha and beta peaks from 16 members of each sex. Time-frequency decompositions showed that in quiet discrimination, females displayed stronger early mu-alpha synchronization, whereas males showed stronger mu-beta desynchronization. Findings indicate that early attentional mechanisms for speech discrimination were characterized by sensorimotor inhibition in females and predictive sensorimotor activation in males. Both sexes showed stronger early sensorimotor inhibition in noisy discrimination conditions versus in quiet, suggesting sensory gating of the noise. However, the difference in neural activation between quiet and noisy conditions was greater in males than females. Though sex differences appear unrelated to behavioral accuracy, they suggest that males and females exhibit early sensorimotor processing for speech discrimination that is fundamentally different, yet similarly adaptable to adverse conditions. Findings have implications for understanding variability in neuroimaging data and the male prevalence in various neurodevelopmental disorders with inhibitory dysfunction.

Trait related sensorimotor deficits in people who stutter: An EEG investigation of μ rhythm dynamics during spontaneous fluency

Stuttering is associated with compromised sensorimotor control (i.e., internal modeling) across the dorsal stream and oscillations of EEG mu (μ) rhythms have been proposed as reliable indices of anterior dorsal stream processing. The purpose of this study was to compare μ rhythm oscillatory activity between (PWS) and matched typically fluent speakers (TFS) during spontaneously fluent overt and covert speech production tasks. Independent component analysis identified bilateral μ components from 24/27 PWS and matched TFS that localized over premotor cortex. Time-frequency analysis of the left hemisphere μ clusters demonstrated significantly reduced μ-α and μ-β ERD (pCLUSTER < 0.05) in PWS across the time course of overt and covert speech production, while no group differences were found in the right hemisphere in any condition. Results were interpreted through the framework of State Feedback Control. They suggest that weak forward modeling and evaluation of sensory feedback across the time course of speech production characterizes the trait related sensorimotor impairment in PWS. This weakness is proposed to represent an underlying sensorimotor instability that may predispose the speech of PWS to breakdown.

EEG Mu (µ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults

Stuttering is linked to sensorimotor deficits related to internal modeling mechanisms. This study compared spectral power and oscillatory activity of EEG mu (μ) rhythms between persons who stutter (PWS) and controls in listening and auditory discrimination tasks. EEG data were analyzed from passive listening in noise and accurate (same/different) discrimination of tones or syllables in quiet and noisy backgrounds. Independent component analysis identified left and/or right μ rhythms with characteristic alpha (α) and beta (β) peaks localized to premotor/motor regions in 23 of 27 people who stutter (PWS) and 24 of 27 controls. PWS produced μ spectra with reduced β amplitudes across conditions, suggesting reduced forward modeling capacity. Group time-frequency differences were associated with noisy conditions only. PWS showed increased μ-β desynchronization when listening to noise and early in discrimination events, suggesting evidence of heightened motor activity that might be related to forward modeling deficits. PWS also showed reduced μ-α synchronization in discrimination conditions, indicating reduced sensory gating. Together these findings indicate spectral and oscillatory analyses of μ rhythms are sensitive to stuttering. More specifically, they can reveal stuttering-related sensorimotor processing differences in listening and auditory discrimination that also may be influenced by basal ganglia deficits.