IntroductionDuring sensorimotor adaptation, participants respond to a persistent sensory error by shifting behavior to oppose the error. This phenomenon has been measured in multiple motor tasks in which sensory feedback is experimentally altered to artificially introduce an error. Tasks involving multiple cycles of altered and unaltered feedback have been used in the arm reaching domain to understand the mechanisms of un-learning and re-learning a response to an error, but re-learning within a single session has not been studied in the domain of fundamental frequency (f0) control during speech.MethodsIn this study, participants responded to three alternating blocks of f0-shifted and unshifted auditory feedback during a single-word speech task.ResultsIt was found that on average, adaptation magnitude decreased in the second and third blocks of shifted feedback compared to the first. This illustrates an attenuation effect similar to that observed in studies of implicit learning in arm reaching tasks.DiscussionThese results support the understanding of f0 control as an implicit learning phenomenon and help place f0 control in the context of motor control in general.

A central challenge in systems neuroscience is understanding how computational mechanisms-including those implemented within a single brain region-interact to produce behavior. For example, prior work in the literature attributes many computational functions to the cerebellum, but these functions have been tested in isolation and it remains unclear how they jointly contribute to motor control. Here, we test several established hypotheses of cerebellar function: internal modeling, timing of movement dynamics, sensory-error processing, delay processing, and multimodal integration. We first formalize these functions as mechanistic parameters within a computational model of speech motor control. We then use this formalism to investigate the relative contribution of each function to the abnormal speech corrective response seen in adults with cerebellar degeneration during perturbed auditory feedback. We find the following functions explain most of the behavioral differences: internal modeling, timing of movement dynamics, and multimodal integration. We also show that the key mechanisms have a trade-off relationship, and that cerebellar degeneration modulates those trade-off strengths and boundaries. These results both elaborate the mechanistic function of the cerebellum in speech feedback control and, more broadly, demonstrate the promise of using this paradigm to simultaneously test competing theories of neural function underlying behavior.

Introduction: Laryngeal dystonia (LD) is a neurological voice disorder marked by strained voice quality, pitch instability, and sudden voice breaks, yet the mechanisms underlying impaired vocal control are poorly understood. One key process, known as pitch centering, reflects the central nervous system's ability to correct early pitch deviations during an utterance by converging toward an intended target. While pitch centering provides a sensitive window into the neural control of spontaneous speech, it remains unexamined in patients with LD and is presumed to contribute to disordered regulation of voice production. Methods: Here, we examined pitch centering in 24 individuals with LD [adductor LD (n = 20), abductor LD (n = 3), or both (n = 1)] compared to 29 healthy controls. The primary outcome measures were: (1) Pitch centering and (2) Pitch movement. Pitch centering was defined as the difference in the absolute values of initial (0-50 ms) and mid-trial (150-200 ms) pitch. Positive values (centering > 0) indicated a shift toward the median pitch defined as centering trials. Pitch movement was defined as the difference between mid-trial and initial pitch. In a subset of trials, we observed negative values of centering reflecting movement away from intended pitch targets, which we defined as anticentering trials. An additional subset of trials was defined as overshoot trials, instances where the normalized pitch movement crosses the median pitch at mid-trial. Results: Initial pitch deviation (p < 0.0001) and pitch movement magnitude (p < 0.0001) were significantly greater in individuals with LD compared to controls across all trials. Importantly, individuals with LD exhibited more pronounced centering responses compared to controls, with greater centering magnitude observed by a significant group-by-tercile interaction (p = 0.028). Individuals with LD and controls showed similar distributions of centering and anticentering trial types. However, LD patients exhibited significantly greater centering magnitude compared to controls across each trial type. Discussion: These findings offer valuable insights into speech motor and predictive control processes in LD, with potential implications for clinical assessment and treatment strategies aimed at improving patient quality of life.

The human sensorimotor system has a remarkable ability to learn movements from sensory experience. A prominent example is sensorimotor adaptation, learning that characterizes the sensorimotor system's response to persistent sensory errors by adjusting future movements to compensate for those errors. A component of sensorimotor adaptation is implicit (i.e., the learner is unaware of the learning) which has been suggested to result from sensory prediction errors-discrepancies between predicted sensory consequences of motor commands and actual sensory feedback. However, neurophysiological evidence that sensory prediction errors drive adaptation has never been directly demonstrated. Here, we examined prediction errors via magnetoencephalography imaging of the auditory cortex during sensorimotor adaptation of speech to altered auditory feedback, an entirely implicit adaptation task. Specifically, we measured how speaking-induced suppression (SIS)-a neural representation of auditory prediction errors-changed over the trials of the adaptation experiment. In both male and female speakers, reduction in SIS (reflecting larger prediction errors) during the early learning phase compared with the initial unaltered feedback phase positively correlated with behavioral adaptation extents, suggesting larger prediction errors were associated with more learning. In contrast, such a reduction in SIS was not found in a control experiment in which participants heard unaltered feedback and thus did not adapt. In addition, in some participants who reached a plateau in the late learning phase, SIS increased, demonstrating that prediction errors were minimal when there was no further adaptation. Together, these findings provide the first direct neurophysiological evidence for the hypothesis that prediction errors drive sensorimotor adaptation.

Changes in brain network function have been clearly demonstrated in patients with Alzheimer's disease (AD). Specifically, previous electrophysiological studies have shown that delta and theta oscillatory activity increases in AD, while alpha and beta activity reduces, compared to controls. These frequency-specific abnormalities have also shown to be region dependent, where low frequency delta-theta increases are more predominant in the frontal cortices while alpha and beta reductions are more predominant in the temporal and parietal cortices, in AD. What is unknown is how consistent these frequency-specific and region-dependent abnormalities are, across different metrics of oscillatory activity ranging from local to long-range connectivity. Here, in a well characterized, AD biomarker positive cohort of 77 AD patients and age-matched controls ( n  = 90), we used magnetoencephalography (MEG) to examine the local and long-range oscillatory abnormalities. Specifically, source-space reconstructed MEG signal for 40 cortical regions of Brainnetome was used to compute three different metric: local neural synchrony estimated as regional spectral power (SP); long-range synchrony at slow time-scale estimated from amplitude-envelope correlation (AEC); and long-range synchrony at fast time-scale estimated from imaginary coherence (IMCOH). Each measure was computed for 2–7 Hz (delta-theta), 8–12 Hz (alpha), and 15–29 Hz (beta) bands. Consistent with previous results, we found that increased delta-theta and reduced alpha and beta oscillatory activity patterns in AD compared to controls (Figure 1A). A conjoint analysis, in which we examined the common spatial patterns across different metrics of connectivity demonstrated that the frequency-specific patterns have consistent regional dependencies (Fig-1B). For example, the highest activity increases in delta-theta was found in the dorsal frontal and anterior cingulate cortices, while the greatest reductions in alpha was consistently found in the inferolateral temporal cortices and posterior temporoparietal regions. Reductions in beta also showed regional consistencies like alpha. Our results show that frequency-specific, region-dependent neurophysiological manifestations in AD are conserved across different synchronization paradigms that contribute to the functional architecture of neural networks. Importantly, the current findings define unified region-of-interests within each frequency component (delta-theta, alpha and beta) that can be further interrogated in future studies to investigate other pathobiological relationships in AD.

BACKGROUND:Agency is the awareness of being the originator of one's own thoughts and actions. Patients with schizophrenia (SZ) show deficits in agency that contribute to distortions in reality monitoring (RM) (distinguishing self-generated from externally produced information) and psychotic symptoms. Agency is also critical for speech monitoring (SM) (monitoring what we hear ourselves say while speaking). For example, disruptions in agency that manifest as hallucinations are thought to result from the misattribution of the source of patients' inner thoughts/speech as external voices. METHODS:We used magnetoencephalography (MEG) to assess agency during RM and SM tasks. In healthy control participants (HCs) during SM, the auditory cortical (A1) response is smaller while speaking (speak condition) compared with listening to the same speech (listen condition). This is known as the speaking-induced suppression (SIS) M100 response, which is measured using MEG 100 ms after speech onset. RESULTS:During RM, patients with SZ (N = 30) showed impairments in both self-agency (identification of self-generated information) and external agency (identification of externally produced information) compared with HCs (N = 30). During SM, patients with SZ failed to enhance M100 responses during the listen condition, resulting in weakened SIS-that is, smaller M100 listen minus speak differences. Weakened SIS predicted worsening hallucination severity. CONCLUSIONS:Patients with SZ showed degraded neural M100 responses in A1 during the listen condition, which drove impaired SIS (i.e., smaller M100 listen minus speak differences). Impaired SIS indicated degraded auditory sensory predictions, making it more likely for patients with SZ to misattribute the source of inner thoughts/speech as externally derived, giving rise to disruptions in agency during RM and more severe hallucinations.

Past studies have explored formant centering, a corrective behavior of convergence over the duration of an utterance toward the formants of a putative target vowel. In this study, we establish the existence of a similar centering phenomenon for pitch in healthy elderly controls and examine how such corrective behavior is altered in Alzheimer's Disease (AD). We found the pitch centering response in healthy elderly was similar when correcting pitch errors below and above the target (median) pitch. In contrast, patients with AD showed an asymmetry with a larger correction for the pitch errors below the target phonation than above the target phonation. These findings indicate that pitch centering is a robust compensation behavior in human speech. Our findings also explore the potential impacts on pitch centering from neurodegenerative processes impacting speech in AD.

Based on historic observations that children with reading disabilities were disproportionately both male and non-right-handed, and that early life insults of the left hemisphere were more frequent in boys and non-right-handed children, it was proposed that early focal neuronal injury disrupts typical patterns of motor hand and language dominance and in the process produces developmental dyslexia. To date, these theories remain controversial. We revisited these earliest theories in a contemporary manner, investigating demographics associated with reading disability, and in a subgroup with and without reading disability, compared structural imaging as well as patterns of activity during tasks of verb generation and non-word repetition using magnetoencephalography source imaging. In a large group of healthy aging adults (n = 282; average age 72.3), we assessed reading ability via the Adult Reading History Questionnaire and found that non-right-handedness and male sex significantly predicted endorsed reading disability. In a subset of participants from the larger cohort who endorsed reading disability (n = 14) and a group who denied reading disability (n = 22), we compared structural and functional imaging data. We failed to detect structural differences in volumetric brain morphometry analyses, however we observed decreased neural activity on magnetoencephalography within the reading disability group. The detected differences were largely restricted to left hemisphere ventral occipito-temporal and posterior-lateral temporal cortices, the visual word form area and middle temporal gyrus, regions implicated in developmental dyslexia. Moreover, these observed disruptions occurred in a focal, network-specific manner, preferentially disturbing the ventral/sight reading recognition pathway, resulting in a pattern of regional anomalous lateralization of function that distinguished the reading disability cohort from normal readers. Collectively, the results presented here align with old theories regarding the etiology of developmental dyslexia and highlight how results from investigating neurodevelopmental differences in healthy aging individuals can powerfully contribute towards our overall understanding of neurodevelopment and neurodiversity.

Behavioral speech tasks have been widely used to understand the mechanisms of speech motor control in typical speakers as well as in various clinical populations. However, determining which neural functions differ between typical speakers and clinical populations based on behavioral data alone is difficult because multiple mechanisms may lead to the same behavioral differences. For example, individuals with cerebellar ataxia (CA) produce atypically large compensatory responses to pitch perturbations in their auditory feedback, compared to typical speakers, but this pattern could have many explanations. Here, computational modeling techniques were used to address this challenge. Bayesian inference was used to fit a state feedback control (SFC) model of voice fundamental frequency (fo) control to the behavioral pitch perturbation responses of speakers with CA and typical speakers. This fitting process resulted in estimates of posterior likelihood distributions for five model parameters (sensory feedback delays, absolute and relative levels of auditory and somatosensory feedback noise, and controller gain), which were compared between the two groups. Results suggest that the speakers with CA may proportionally weight auditory and somatosensory feedback differently from typical speakers. Specifically, the CA group showed a greater relative sensitivity to auditory feedback than the control group. There were also large group differences in the controller gain parameter, suggesting increased motor output responses to target errors in the CA group. These modeling results generate hypotheses about how CA may affect the speech motor system, which could help guide future empirical investigations in CA. This study also demonstrates the overall proof-of-principle of using this Bayesian inference approach to understand behavioral speech data in terms of interpretable parameters of speech motor control models.

Self-agency is the awareness of being the agent of one's own thoughts and actions. Self-agency is essential for interacting with the outside world (reality-monitoring). The medial prefrontal cortex (mPFC) is thought to be one neural correlate of self-agency. We investigated whether mPFC activity can causally modulate self-agency on two different tasks of speech-monitoring and reality-monitoring. The experience of self-agency is thought to result from making reliable predictions about the expected outcomes of one’s own actions. This self-prediction ability is necessary for the encoding and memory retrieval of one’s own thoughts during reality-monitoring to enable accurate judgments of self-agency. This self-prediction ability is also necessary for speech-monitoring where speakers consistently compare auditory feedback (what we hear ourselves say) with what we expect to hear while speaking. In this study, 30 healthy participants are assigned to either 10 Hz repetitive transcranial magnetic stimulation (rTMS) to enhance mPFC excitability (N = 15) or 10 Hz rTMS targeting a distal temporoparietal site (N = 15). High-frequency rTMS to mPFC enhanced self-predictions during speech-monitoring that predicted improved self-agency judgments during reality-monitoring. This is the first study to provide robust evidence for mPFC underlying a causal role in self-agency, that results from the fundamental ability of improving self-predictions across two different tasks.

Alzheimer’s disease (AD) carries an increased risk of seizures and subclinical epileptiform activity (Vossel et al. 2016). Network hyperexcitability which is the underlying phenomenon of epileptic manifestations is thought to contribute to AD pathophysiological processes. Recently we demonstrated that greater degree of neural synchronization deficits within 2-8Hz range of frequency oscillations are sensitive indicators of network hyperexcitability (Ranasinghe et al. 2021). Here, we sought to examine the high frequency gamma band deficits associated with network hyperexcitability in AD patients. Specifically, we quantified Phase Amplitude Coupling (PAC) between the amplitude of gamma oscillations (30-40Hz); with the phase of 2-8Hz oscillations) (Figure 1). We used 60s resting-state magnetoencephalography (MEG) recordings from 48 AD patients (n = 22, with subclinical epileptiform activity, AD-EPI+; n = 28 without subclinical epileptiform activity, AD-EPI-), and 35 age-matched controls. We computed PAC for each of 68 cortical regions (Desikan et al. 2006) on source-space reconstructed MEG signal using the mean vector length (Canolty et al. 2006). Permutation cluster test was performed for statistical comparisons between AD patients vs. age matched controls, and AD-EPI+ vs. AD-EPI-. Patients with AD showed significantly higher theta (4-8 Hz)-gamma coupling in the left parahippocampal and right caudal-middle frontal regions. Importantly, this increased left parahippocampal theta-gamma coupling was significantly higher in AD-EPI+ patients than in AD-EPI-. AD-EPI+ also showed higher alpha (8-12Hz)-gamma coupling in the right parahippocampal region compared to AD-EPI- (Figure 2). These results not only identify gamma band coupling deficits specifically localized to medial temporal regions which are the earliest affected regions in AD pathophysiology but also delineate the associated vulnerabilities of network hyperexcitability in AD.

Upon perceiving sensory errors during movements, the human sensorimotor system updates future movements to compensate for the errors, a phenomenon called sensorimotor adaptation. One component of this adaptation is thought to be driven by sensory prediction errors-discrepancies between predicted and actual sensory feedback. However, the mechanisms by which prediction errors drive adaptation remain unclear. Here, auditory prediction error-based mechanisms involved in speech auditory-motor adaptation were examined via the feedback aware control of tasks in speech (FACTS) model. Consistent with theoretical perspectives in both non-speech and speech motor control, the hierarchical architecture of FACTS relies on both the higher-level task (vocal tract constrictions) as well as lower-level articulatory state representations. Importantly, FACTS also computes sensory prediction errors as a part of its state feedback control mechanism, a well-established framework in the field of motor control. We explored potential adaptation mechanisms and found that adaptive behavior was present only when prediction errors updated the articulatory-to-task state transformation. In contrast, designs in which prediction errors updated forward sensory prediction models alone did not generate adaptation. Thus, FACTS demonstrated that 1) prediction errors can drive adaptation through task-level updates, and 2) adaptation is likely driven by updates to task-level control rather than (only) to forward predictive models. Additionally, simulating adaptation with FACTS generated a number of important hypotheses regarding previously reported phenomena such as identifying the source(s) of incomplete adaptation and driving factor(s) for changes in the second formant frequency during adaptation to the first formant perturbation. The proposed model design paves the way for a hierarchical state feedback control framework to be examined in the context of sensorimotor adaptation in both speech and non-speech effector systems.

COPYRIGHT © 2023 Houde, Ménard, Jones, Shiller and Tian. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: New perspectives on the role of sensory feedback in speech production

Alzheimer's disease (AD) is a neurodegenerative disease involving cognitive impairment and abnormalities in speech and language. Here, we examine how AD affects the fidelity of auditory feedback predictions during speaking. We focus on the phenomenon of speaking-induced suppression (SIS), the auditory cortical responses' suppression during auditory feedback processing. SIS is determined by subtracting the magnitude of auditory cortical responses during speaking from listening to playback of the same speech. Our state feedback control (SFC) model of speech motor control explains SIS as arising from the onset of auditory feedback matching a prediction of that feedback onset during speaking, a prediction that is absent during passive listening to playback of the auditory feedback. Our model hypothesizes that the auditory cortical response to auditory feedback reflects the mismatch with the prediction: small during speaking, large during listening, with the difference being SIS. Normally, during speaking, auditory feedback matches its predictions, then SIS will be large. Any reductions in SIS will indicate inaccuracy in auditory feedback prediction not matching the actual feedback. We investigated SIS in AD patients [n = 20; mean (SD) age, 60.77 (10.04); female (%), 55.00] and healthy controls [n = 12; mean (SD) age, 63.68 (6.07); female (%), 83.33] through magnetoencephalography (MEG)-based functional imaging. We found a significant reduction in SIS at ∼100 ms in AD patients compared with healthy controls (linear mixed effects model, F (1,57.5) = 6.849, p = 0.011). The results suggest that AD patients generate inaccurate auditory feedback predictions, contributing to abnormalities in AD speech.

Overlapping clinical presentations in primary progressive aphasia (PPA) variants present challenges for diagnosis and understanding pathophysiology, particularly in the early stages of the disease when behavioral (speech) symptoms are not clearly evident. Divergent atrophy patterns (temporoparietal degeneration in logopenic variant lvPPA, frontal degeneration in nonfluent variant nfvPPA) can partially account for differential speech production errors in the two groups in the later stages of the disease. While the existing dogma states that neurodegeneration is the root cause of compromised behavior and cortical activity in PPA, the extent to which neurophysiological signatures of speech dysfunction manifest independent of their divergent atrophy patterns remain unknown. We test the hypothesis that nonword deficits in lvPPA and nfvPPA arise from distinct patterns of neural oscillations that are unrelated to atrophy. We use a novel structure-function imaging approach integrating magnetoencephalographic imaging of neural oscillations during a non-word repetition task with voxel-based morphometry-derived measures of gray matter volume to isolate neural oscillation abnormalities independent of atrophy. We find reduced beta band neural activity in left temporal regions associated with the late stages of auditory encoding unique to patients with lvPPA and reduced high-gamma neural activity over left frontal regions associated with the early stages of motor preparation in patients with nfvPPA. Neither of these patterns of reduced cortical oscillations was explained by cortical atrophy in our statistical model. These findings highlight the importance of structure-function imaging in revealing neurophysiological sequelae in early stages of dementia when neither structural atrophy nor behavioral deficits are clinically distinct.

Laryngeal Dystonia is a debilitating disorder of voicing in which the laryngeal muscles are intermittently in spasm resulting in involuntary interruptions during speech. The central pathophysiology of laryngeal dystonia, underlying computational impairments in vocal motor control, remains poorly understood. Although prior imaging studies have found aberrant activity in the central nervous system during phonation in patients with laryngeal dystonia, it is not known at what timepoints during phonation these abnormalities emerge and what function may be impaired. To investigate this question, we recruited 22 adductor laryngeal dystonia patients (15 female, age range = 28.83-72.46 years) and 18 controls (8 female, age range = 27.40-71.34 years). We leveraged the fine temporal resolution of magnetoencephalography to monitor neural activity around glottal movement onset, subsequent voice onset and after the onset of pitch feedback perturbations. We examined event-related beta-band (12-30 Hz) and high-gamma band (65-150 Hz) neural oscillations. Prior to glottal movement onset, we observed abnormal frontoparietal motor preparatory activity. After glottal movement onset, we observed abnormal activity in somatosensory cortex persisting through voice onset. Prior to voice onset and continuing after, we also observed abnormal activity in the auditory cortex and the cerebellum. After pitch feedback perturbation onset, we observed no differences between controls and patients in their behavioural responses to the perturbation. But in patients, we did find abnormal activity in brain regions thought to be involved in the auditory feedback control of vocal pitch (premotor, motor, somatosensory and auditory cortices). Our study results confirm the abnormal processing of somatosensory feedback that has been seen in other studies. However, there were several remarkable findings in our study. First, patients have impaired vocal motor activity even before glottal movement onset, suggesting abnormal movement preparation. These results are significant because: (i) they occur before movement onset, abnormalities in patients cannot be ascribed to deficits in vocal performance, and (ii) they show that neural abnormalities in laryngeal dystonia are more than just abnormal responses to sensory feedback during phonation as has been hypothesised in some previous studies. Second, abnormal auditory cortical activity in patients begins even before voice onset, suggesting abnormalities in setting up auditory predictions before the arrival of auditory feedback at voice onset. Generally, activation abnormalities identified in key brain regions within the speech motor network around various phonation events not only provide temporal specificity to neuroimaging phenotypes in laryngeal dystonia but also may serve as potential therapeutic targets for neuromodulation.

Primary progressive aphasia (PPA) is a clinical syndrome in which patients progressively lose speech and language abilities. Three variants are recognized: logopenic (lvPPA), associated with phonology and/or short-term verbal memory deficits accompanied by left temporo-parietal atrophy; semantic (svPPA), associated with semantic deficits and anterior temporal lobe (ATL) atrophy; non-fluent (nfvPPA) associated with grammar and/or speech-motor deficits and inferior frontal gyrus (IFG) atrophy. Here, we set out to investigate whether the three variants of PPA can be dissociated based on error patterns in a single language task. We recruited 21 lvPPA, 28 svPPA, and 24 nfvPPA patients, together with 31 healthy controls, and analyzed their performance on an auditory noun-to-verb generation task, which requires auditory analysis of the input, access to and selection of relevant lexical and semantic knowledge, as well as preparation and execution of speech. Task accuracy differed across the three variants and controls, with lvPPA and nfvPPA having the lowest and highest accuracy, respectively. Critically, machine learning analysis of the different error types yielded above-chance classification of patients into their corresponding group. An analysis of the error types revealed clear variant-specific effects: lvPPA patients produced the highest percentage of “not-a-verb” responses and the highest number of semantically related nouns (production of baseball instead of throw to noun ball); in contrast, svPPA patients produced the highest percentage of “unrelated verb” responses and the highest number of light verbs (production of take instead of throw to noun ball). Taken together, our findings indicate that error patterns in an auditory verb generation task are associated with the breakdown of different neurocognitive mechanisms across PPA variants. Specifically, they corroborate the link between temporo-parietal regions with lexical processing, as well as ATL with semantic processes. These findings illustrate how the analysis of pattern of responses can help PPA phenotyping and heighten diagnostic sensitivity, while providing insights on the neural correlates of different components of language.

Abstract Background: Alzheimer’s disease (AD) is a neurodegenerative disease involving cognitive impairment and abnormalities in speech and language. Here, we examine how AD affects the fidelity of auditory feedback predictions during speaking. We focus on the phenomenon of speaking-induced suppression (SIS), the auditory cortical responses’ suppression during auditory feedback processing. SIS is determined by subtracting the magnitude of auditory cortical responses during speaking from listening to playback of the same speech. Our state feedback control model of speech motor control explains SIS as arising from the onset of auditory feedback matching a prediction of that feedback onset during speaking – a prediction that is absent during passive listening to playback of the auditory feedback. Our model hypothesizes that the auditory cortical response to auditory feedback reflects the mismatch with the prediction: small during speaking, large during listening, with the difference being SIS. Normally, during speaking, auditory feedback matches its predictions, then SIS will be large. Any reductions in SIS will indicate inaccuracy in auditory feedback prediction not matching the actual feedback. Methods: We investigated SIS in AD patients (n = 20; mean (SD) age, 60.77 (10.04); female (%), 55.00) and healthy controls (n = 12; mean (SD) age, 63.68 (6.07); female (%), 83.33) through magnetoencephalography-based functional imaging. Results: We found a significant reduction in SIS at approximately 100 ms in AD patients compared to healthy controls (linear mixed effects model, F(1, 57.5) = 6.849, P= 0.011). Conclusions: The results suggest that AD patients generate inaccurate auditory feedback predictions, contributing to abnormalities in AD speech.

Primary Progressive Aphasia (PPA) is a clinical syndrome in which patients progressively lose speech and language abilities. The non-fluent variant of PPA (nfvPPA) is characterised by impaired motor speech and agrammatism. To date, no study in nfvPPA patients has either examined speech motor control behaviour or imaged the speech motor control network during vocal production. Here, we did this using a novel structure-function imaging approach integrating magnetoencephalographic imaging of neural oscillations with voxel-based morphometry (VBM). We examined task-induced non-phase-locked neural oscillatory activity during a vocal motor control task, where participants were prompted to phonate the vowel /□/ for ∼2.4s while the pitch of their auditory feedback was shifted either up or down by 100 cents for a period of 400ms mid-utterance. Participants were 18 nfvPPA patients (14 female, mean age = 67.79 ± 8.02 years) and 17 controls (13 female, mean age = 64.81 ± 5.76 years). Patients showed a smaller compensation response to pitch perturbation than controls (p < 0.05). Task-induced neural oscillations across five frequency bands were reconstructed in source space for each subject during pitch feedback perturbation. Patients exhibited reduced task-induced alpha-band (8-12Hz) neural activity unrelated to their atrophy patterns, in the right temporal lobe and the right temporoparietal junction (p < 0.01) from 250ms to 750ms after pitch perturbation onset. Patients also showed increased task-induced beta-band (12-30Hz) activity also unrelated to cortical atrophy in the left dorsal sensorimotor cortex, left premotor cortex and the left supplementary motor area (p < 0.01) from 50ms to 150ms after pitch perturbation onset. Reduced average alpha-band power at the peak voxel in the temporoparietal cluster in the right hemisphere could predict speech motor impairment in patients ( β = 3.41, F = 8.31, p = 0.0128) whereas increased average beta-band power at the peak voxel in the left dorsal sensorimotor cluster could not ( β = -1.75, F = 1.72, p = 0.2123). Collectively, these results suggest significant disruption in sensorimotor integration during vocal production in nfvPPA patients which occurs unrelated to patterns of atrophy. These findings highlight how multimodal structure-function imaging in PPA enhances our understanding of its pathophysiological sequelae.