The left inferior frontal gyrus is causally linked to vocal feedback control: evidence from high-definition transcranial alternating current stimulation

Pars Opercularis Underlies Efferent Predictions and Successful Auditory Feedback Processing in Speech: Evidence From Left-Hemisphere Stroke

Hearing one's own speech allows for acoustic self-monitoring in real time. Left-hemisphere motor planning regions are thought to give rise to efferent predictions that can be compared to true feedback in sensory cortices, resulting in neural suppression commensurate with the degree of overlap between predicted and actual sensations. Sensory prediction errors thus serve as a possible mechanism of detection of deviant speech sounds, which can then feed back into corrective action, allowing for online control of speech acoustics. The goal of this study was to assess the integrity of this detection-correction circuit in persons with aphasia (PWA) whose left-hemisphere lesions may limit their ability to control variability in speech output. We recorded magnetoencephalography (MEG) while 15 PWA and age-matched controls spoke monosyllabic words and listened to playback of their utterances. From this, we measured speaking-induced suppression of the M100 neural response and related it to lesion profiles and speech behavior. Both speaking-induced suppression and cortical sensitivity to deviance were preserved at the group level in PWA. PWA with more spared tissue in pars opercularis had greater left-hemisphere neural suppression and greater behavioral correction of acoustically deviant pronunciations, whereas sparing of superior temporal gyrus was not related to neural suppression or acoustic behavior. In turn, PWA who made greater corrections had fewer overt speech errors in the MEG task. Thus, the motor planning regions that generate the efferent prediction are integral to performing corrections when that prediction is violated.

Aligning Event-Related Potentials with Transcranial Alternating Current Stimulation for Modulation-a Review

This review aims to demonstrate the connections between event-related potentials (ERPs), event-related oscillations (EROs), and non-invasive brain stimulation (NIBS), with a specific focus on transcranial alternating current stimulation (tACS). We begin with a short examination and discussion of the relation between ERPs and EROs. Then, we investigate the diverse fields of NIBS, highlighting tACS as a potent tool for modulating neural oscillations and influencing cognitive performance. Emphasizing the impact of tACS on individual ERP components, this article offers insights into the potential of conventional tACS for targeted stimulation of single ERP components. Furthermore, we review recent articles that explore a novel approach of tACS: ERP-aligned tACS. This innovative technique exploits the temporal precision of ERP components, aligning tACS with specific neural events to optimize stimulation effects and target the desired neural response. In conclusion, this review combines current knowledge to explore how ERPs, EROs, and NIBS interact, particularly highlighting the modulatory possibilities offered by tACS. The incorporation of ERP-aligned tACS introduces new opportunities for future research, advancing our understanding of the complex connection between neural oscillations and cognitive processes.

Using altered auditory feedback to study pitch compensation and adaptation in tonal language speakers

Human speech production is strongly influenced by the auditory feedback it generates. Auditory feedback-what we hear when we speak-enables us to learn and maintain speaking skills and to rapidly correct errors in our speech. Over the last three decades, the real-time altered auditory feedback (AAF) paradigm has gained popularity as a tool to study auditory feedback control during speech production. This method involves changing a speaker's speech and feeding it back to them in near real time. More than 50% of the world's population speak tonal languages, in which the pitch or tone used to pronounce a word can change its meaning. This review article aims to offer an overview of the progression of AAF paradigm as a method to study pitch motor control among speakers of tonal languages. Eighteen studies were included in the current mini review and were compared based on their methodologies and results. Overall, findings from these studies provide evidence that tonal language speakers can compensate and adapt when receiving inconsistent and consistent pitch perturbations. Response magnitude and latency are influenced by a range of factors. Moreover, by combining AAF with brain stimulation and neuroimaging techniques, the neural basis of pitch motor control in tonal language speakers has been investigated. To sum up, AAF has been demonstrated to be an emerging tool for studying pitch motor control in speakers of tonal languages.

An interpretable model based on graph learning for diagnosis of Parkinson's disease with voice-related EEG

Parkinson's disease (PD) exhibits significant clinical heterogeneity, presenting challenges in the identification of reliable electroencephalogram (EEG) biomarkers. Machine learning techniques have been integrated with resting-state EEG for PD diagnosis, but their practicality is constrained by the interpretable features and the stochastic nature of resting-state EEG. The present study proposes a novel and interpretable deep learning model, graph signal processing-graph convolutional networks (GSP-GCNs), using event-related EEG data obtained from a specific task involving vocal pitch regulation for PD diagnosis. By incorporating both local and global information from single-hop and multi-hop networks, our proposed GSP-GCNs models achieved an averaged classification accuracy of 90.2%, exhibiting a significant improvement of 9.5% over other deep learning models. Moreover, the interpretability analysis revealed discriminative distributions of large-scale EEG networks and topographic map of microstate MS5 learned by our models, primarily located in the left ventral premotor cortex, superior temporal gyrus, and Broca's area that are implicated in PD-related speech disorders, reflecting our GSP-GCN models' ability to provide interpretable insights identifying distinctive EEG biomarkers from large-scale networks. These findings demonstrate the potential of interpretable deep learning models coupled with voice-related EEG signals for distinguishing PD patients from healthy controls with accuracy and elucidating the underlying neurobiological mechanisms.

Right, but not left, posterior superior temporal gyrus is causally involved in vocal feedback control

The posterior superior temporal gyrus (pSTG) has been implicated in the integration of auditory feedback and motor system for controlling vocal production. However, the question as to whether and how the pSTG is causally involved in vocal feedback control is currently unclear. To this end, the present study selectively stimulated the left or right pSTG with continuous theta burst stimulation (c-TBS) in healthy participants, then used event-related potentials to investigate neurobehavioral changes in response to altered auditory feedback during vocal pitch regulation. The results showed that, compared to control (vertex) stimulation, c-TBS over the right pSTG led to smaller vocal compensations for pitch perturbations accompanied by smaller cortical N1 and larger P2 responses. Enhanced P2 responses received contributions from the right-lateralized temporal and parietal regions as well as the insula, and were significantly correlated with suppressed vocal compensations. Surprisingly, these effects were not found when comparing c-TBS over the left pSTG with control stimulation. Our findings provide evidence, for the first time, that supports a causal relationship between right, but not left, pSTG and auditory-motor integration for vocal pitch regulation. This lends support to a right-lateralized contribution of the pSTG in not only the bottom-up detection of vocal feedback errors but also the involvement of driving motor commands for error correction in a top-down manner.

A causal link between left supplementary motor area and auditory-motor control of vocal production: Evidence by continuous theta burst stimulation

The supplementary motor area (SMA) has been implicated in the feedforward control of speech production. Whether this region is involved in speech motor control through auditory feedback, however, remains uncertain. The present event-related potential (ERP) study examined the role of the left SMA in vocal pitch regulation in a causal manner by combining auditory feedback manipulations and neuronavigated continuous theta bust stimulation (c-TBS). After receiving c-TBS over the left SMA or the control site (vertex), twenty young adults vocalized the vowel sound /u/ while hearing their voice unexpectedly pitch-shifted -50 or -200 cents. Compared to the control stimulation, c-TBS over the left SMA led to decreased vocal compensations for pitch perturbations of -50 and -200 cents. A significant decrease of N1 and P2 responses to -200 cents perturbations was also found when comparing active and control stimulation. Major neural generators of decreased P2 responses included the right-lateralized superior and middle temporal gyrus and angular gyrus. Notably, a significant correlation was found between active-control differences in the vocal compensation and P2 responses for the -200 cents perturbations. These findings provide neurobehavioral evidence for a causal link between the left SMA and auditory-motor integration for vocal pitch regulation, suggesting that the left SMA receives auditory feedback information and mediates vocal compensations for feedback errors in a bottom-up manner.