Stuttering severity relates to frontotemporal low-beta synchronization during pre-speech preparation

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.

Identification of the Biomechanical Response of the Muscles That Contract the Most during Disfluencies in Stuttered Speech

Stuttering, affecting approximately 1% of the global population, is a complex speech disorder significantly impacting individuals' quality of life. Prior studies using electromyography (EMG) to examine orofacial muscle activity in stuttering have presented mixed results, highlighting the variability in neuromuscular responses during stuttering episodes. Fifty-five participants with stuttering and 30 individuals without stuttering, aged between 18 and 40, participated in the study. EMG signals from five facial and cervical muscles were recorded during speech tasks and analyzed for mean amplitude and frequency activity in the 5-15 Hz range to identify significant differences. Upon analysis of the 5-15 Hz frequency range, a higher average amplitude was observed in the zygomaticus major muscle for participants while stuttering (p < 0.05). Additionally, when assessing the overall EMG signal amplitude, a higher average amplitude was observed in samples obtained from disfluencies in participants who did not stutter, particularly in the depressor anguli oris muscle (p < 0.05). Significant differences in muscle activity were observed between the two groups, particularly in the depressor anguli oris and zygomaticus major muscles. These results suggest that the underlying neuromuscular mechanisms of stuttering might involve subtle aspects of timing and coordination in muscle activation. Therefore, these findings may contribute to the field of biosensors by providing valuable perspectives on neuromuscular mechanisms and the relevance of electromyography in stuttering research. Further research in this area has the potential to advance the development of biosensor technology for language-related applications and therapeutic interventions in stuttering.

Stuttering-Like Dysfluencies as a Consequence of Long COVID-19

PURPOSE

We present two patients who developed neurogenic stuttering after long COVID-19 related to SARS-CoV-2 infection.

METHODS AND RESULTS

Both patients experienced both physical (e.g., fatigue) and cognitive difficulties, which led to impaired function of attention, lexical retrieval, and memory consolidation. Both patients had new-onset stuttering-like speech dysfluencies: Blocks and repetitions were especially evident at the initial part of words and sentences, sometimes accompanied by effortful and associated movements (e.g., facial grimaces and oro-facial movements). Neuropsychological evaluations confirmed the presence of difficulties in cognitive tasks, while neurophysiological evaluations (i.e., electroencephalography) suggested the presence of "slowed" patterns of brain activity. Neurogenic stuttering and cognitive difficulties were evident for 4-5 months after negativization of SARS-CoV-2 nasopharyngeal swab, with gradual improvement and near-to-complete recovery.

CONCLUSIONS

It is now evident that SARS-CoV-2 infection may significantly involve the central nervous system, also resulting in severe and long-term consequences, even if the precise mechanisms are still unknown. In the present report, long COVID-19 resulted in neurogenic stuttering, as the likely consequence of a "slowed" metabolism of (pre)frontal and sensorimotor brain regions (as suggested by the present and previous clinical evidence). As a consequence, the pathophysiological mechanisms related to the appearance of neurogenic stuttering have been hypothesized, which help to better understand the broader and possible neurological consequences of COVID-19.

Effects of Binaural Beat Stimulation in Adults with Stuttering

In recent decades, several studies have demonstrated a link between stuttering and abnormal electroencephalographic (EEG) β-power in cortex. Effects of exposure to binaural stimuli were studied in adults with stuttering (AWS, n = 6) and fluent participants (n = 6) using EEG, ECG, and speech analysis. During standard reading tasks without stimulation, in controls but not in the AWS group, EEG β-power was significantly higher in the left hemisphere than in the right hemisphere. After stimulation, the power of the β-band in AWS participants in the left hemisphere increased 1.54-fold. The average β-band power within the left frontotemporal area and temporoparietal junction of the cortex after stimulation in AWS participants shows an increase by 1.65-fold and 1.72-fold, respectively. The rate of disfluency dropped significantly immediately after stimulation (median 74.70% of the baseline). Similarly, the speech rate significantly increased immediately after stimulation (median 133.15%). We show for the first time that auditory binaural beat stimulation can improve speech fluency in AWS, and its effect is proportional to boost in EEG β-band power in left frontotemporal and temporoparietal junction of cortex. Changes in β-power were detected immediately after exposure and persisted for 10 min. Additionally, these effects were accompanied by a reduction in stress levels.

Inefficient speech-motor control affects predictive speech comprehension: atypical electrophysiological correlates in stuttering

Listeners predict upcoming information during language comprehension. However, how this ability is implemented is still largely unknown. Here, we tested the hypothesis proposing that language production mechanisms have a role in prediction. We studied 2 electroencephalographic correlates of predictability during speech comprehension-pre-target alpha-beta (8-30 Hz) power decrease and the post-target N400 event-related potential effect-in a population with impaired speech-motor control, i.e. adults who stutter (AWS), compared to typically fluent adults (TFA). Participants listened to sentences that could either constrain towards a target word or not, modulating its predictability. As a complementary task, participants also performed context-driven word production. Compared to TFA, AWS not only displayed atypical neural responses in production, but, critically, they showed a different pattern also in comprehension. Specifically, while TFA showed the expected pre-target power decrease, AWS showed a power increase in frontal regions, associated with speech-motor control. In addition, the post-target N400 effect was reduced for AWS with respect to TFA. Finally, we found that production and comprehension power changes were positively correlated in TFA, but not in AWS. Overall, the results support the idea that processes and neural structures prominently devoted to speech planning also support prediction during speech comprehension.