Background Alzheimer’s disease (AD) is the most common form of dementia, progressively impairing cognitive abilities. While neuroimaging studies have revealed functional abnormalities in AD, how these relate to aberrant neuronal circuit mechanisms remains unclear. Using magnetoencephalography imaging we documented abnormal local neural synchrony patterns in patients with AD. To identify global abnormal biophysical mechanisms underlying the spatial and spectral electrophysiological patterns in AD, we estimated the parameters of a biophysical spectral graph model (SGM). Methods SGM is an analytic neural mass model that describes how long-range fiber projections in the brain mediate the excitatory and inhibitory activity of local neuronal subpopulations. Unlike other coupled neuronal mass models, the SGM is linear, available in closed-form, and parameterized by a small set of biophysical interpretable global parameters. This facilitates their rapid and unambiguous inference which we performed here on a well-characterized clinical population of patients with AD ( N = 88, age = 62.73 +/- 8.64 years) and a cohort of age-matched controls ( N = 88, age = 65.07 +/- 9.92 years). Results Patients with AD showed significantly elevated long-range excitatory neuronal time scales, local excitatory neuronal time scales and local inhibitory neural synaptic strength. The long-range excitatory time scale had a larger effect size, compared to local excitatory time scale and inhibitory synaptic strength and contributed highest for the accurate classification of patients with AD from controls. Furthermore, increased long-range time scale was associated with greater deficits in global cognition. Conclusions These results demonstrate that long-range excitatory time scale of neuronal activity, despite being a global measure, is a key determinant in the local spectral signatures and cognition in the human brain, and how it might be a parsimonious factor underlying altered neuronal activity in AD. Our findings provide new insights into mechanistic links between abnormal local spectral signatures and global connectivity measures 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.

While animal models of Alzheimer's disease (AD) have shown altered gamma oscillations (similar to 40 Hz) in local neural circuits, the low signal-to-noise ratio of gamma in the resting human brain precludes its quantification via conventional spectral estimates. Phase-amplitude coupling (PAC) indicating the dynamic integration between the gamma amplitude and the phase of low-frequency (4-12 Hz) oscillations is a useful alternative to capture local gamma activity. In addition, PAC is also an index of neuronal excitability as the phase of low-frequency oscillations that modulate gamma amplitude, effectively regulates the excitability of local neuronal firing. In this study, we sought to examine the local neuronal activity and excitability using gamma PAC, within brain regions vulnerable to early AD pathophysiology-entorhinal cortex and parahippocampus, in a clinical population of patients with AD and age-matched controls. Our clinical cohorts consisted of a well-characterized cohort of AD patients (n = 50; age, 60 +/- 8 years) with positive AD biomarkers, and age-matched, cognitively unimpaired controls (n = 35; age, 63 +/- 5.8 years). We identified the presence or the absence of epileptiform activity in AD patients (AD patients with epileptiform activity, AD-EPI+, n = 20; AD patients without epileptiform activity, AD-EPI-, n = 30) using long-term electroencephalography (LTM-EEG) and 1-hour long magnetoencephalography (MEG) with simultaneous EEG. Using the source reconstructed MEG data, we computed gamma PAC as the coupling between amplitude of the gamma frequency (30-40 Hz) with phase of the theta (4-8 Hz) and alpha (8-12 Hz) frequency oscillations, within entorhinal and parahippocampal cortices. We found that patients with AD have reduced gamma PAC in the left parahippocampal cortex, compared to age-matched controls. Furthermore, AD-EPI+ patients showed greater reductions in gamma PAC than AD-EPI- in bilateral parahippocampal cortices. In contrast, entorhinal cortices did not show gamma PAC abnormalities in patients with AD. Our findings demonstrate the spatial patterns of altered gamma oscillations indicating possible region-specific manifestations of network hyperexcitability within medial temporal lobe regions vulnerable to AD pathophysiology. Greater deficits in AD-EPI+ suggests that reduced gamma PAC is a sensitive index of network hyperexcitability in AD patients. Collectively, the current results emphasize the importance of investigating the role of neural circuit hyperexcitability in early AD pathophysiology and explore its potential as a modifiable contributor to AD pathobiology. Prabhu et al. examined phase-amplitude coupling between gamma amplitude and phase of lower frequencies in patients with Alzheimer's disease (AD) and their associations with network hyperexcitability. Theta-gamma coupling in AD was reduced in medial temporal regions (parahippocampus), which is the earliest affected region in AD, and was associated network hyperexcitability. Graphical abstract

Sensory processing dysfunction not only affects most individuals with autism spectrum disorder (ASD), but at least 5% of children without ASD also experience dysfunctional sensory processing. Our understanding of the relationship between sensory dysfunction and resting state brain activity is still emerging. This study compared long-range resting state functional connectivity of neural oscillatory behavior in children aged 8-12 years with autism spectrum disorder (ASD; N=18), those with sensory processing dysfunction (SPD; N=18) who do not meet ASD criteria, and typically developing control participants (TDC; N=24) using magnetoencephalography (MEG). Functional connectivity analyses were performed in the alpha and beta frequency bands, which are known to be implicated in sensory information processing. Group differences in functional connectivity and associations between sensory abilities and functional connectivity were examined. Distinct patterns of functional connectivity differences between ASD and SPD groups were found only in the beta band, but not in the alpha band. In both alpha and beta bands, ASD and SPD cohorts differed from the TDC cohort. Somatosensory cortical beta-band functional connectivity was associated with tactile processing abilities, while higher-order auditory cortical alpha-band functional connectivity was associated with auditory processing abilities. These findings demonstrate distinct long-range neural synchrony alterations in SPD and ASD that are associated with sensory processing abilities. Neural synchrony measures could serve as potential sensitive biomarkers for ASD and SPD.

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.

Abstract Alzheimer’s disease (AD) is the most common form of dementia, progressively impairing memory and cognition. While neuroimaging studies have revealed functional abnormalities in AD, how these relate to aberrant neuronal circuit mechanisms remains unclear. We employed a spectral graph-theory model (SGM) to identify abnormal biophysical markers of neuronal activity in AD. SGM is an analytic model that describes how long-range fiber projections in the brain mediate excitatory and inhibitory activity of local neuronal subpopulations. We estimated SGM parameters that captured the regional power spectra obtained from magnetoencephalography imaging of a well-characterized population of patients with AD and controls. The long-range excitatory time constant was the most important feature for the accurate classification of AD and controls and was associated with global cognitive deficits in AD. These results indicate that a global impairment in the long-range excitatory neurons might be a sufficient factor underlying spatiotemporal alterations of neuronal activity in AD.

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.

Excitation-to-inhibition (E/I) imbalance is believed to be a key contributor of synaptic and network degeneration in Alzheimer’s disease (AD)(Frere and Slutsky, 2018). Extensive preclinical research on transgenic animal models of AD have demonstrated neuronal and circuit level E/I imbalance mediated by amyloid-beta (Aβ) and abnormally phosphorylated tau proteins (Harris et al., 2020; Palop and Mucke, 2016). However, the mechanisms of E/I imbalance leading to disrupted networks and their relationships to Aβ and tau in humans remain poorly understood. In this multimodal imaging study in patients with AD (n=20 AD patients; n=35 age-matched controls; Table-1), we first examined the spectral changes in oscillatory brain rhythms using magnetoencephalography and their relationships to tau and amyloid-beta (Aβ) accumulation in PET imaging (flortaucipir and 11C-PiB, for tau and Aβ, respectively). Next, we estimated parameters of a linear neural mass model (Raj et al., 2020) that best fit the observed spectra, and examined the relationships between model parameters for excitatory and inhibitory neural sub-populations, and tau and Aβ accumulations. We found that neuronal hypoactivity was associated with tau while hyperactivity was associated with Aβ (Figure 1). We also demonstrated E/I imbalance in patients with AD, depicted as abnormal excitatory and inhibitory neuronal parameters in a linear neural mass model that reproduced the empirical macroscopic power spectra (Figure 2). The abnormal excitatory and inhibitory neuronal parameters showed distinct associations with tau and Aβ—higher tau correlated with a longer excitatory time-constant, whereas higher Aβ correlated with a longer inhibitory time-constant (Figure 3). The unique contribution of the collective finding in the current study is to demonstrate how abnormalities in the oscillatory power spectrum in AD is mechanistically linked to impaired function of excitatory and inhibitory neuronal populations that are in turn associated with tau and Aβ accumulations. Neural oscillations are modulators of rate and timing of neuronal spiking and have a key role in governing the neuronal excitability (Siegel et al., 2012). The multimodal neuroimaging in AD patients in the current study demonstrate how different frequency oscillations are distinctly affected by Aβ and tau, and offer new perspectives for network stabilizing therapies.

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.

Background/Introduction: Widespread network disruption has been hypothesized to be an important predictor of outcomes in patients with refractory temporal lobe epilepsy (TLE). Most studies examining functional network disruption in epilepsy have largely focused on the symmetric bidirectional metrics of the strength of network connections. However, a more complete description of network dysfunction impacts in epilepsy requires an investigation of the potentially more sensitive directional metrics of information flow. Methods: This study describes a whole-brain magnetoencephalography-imaging approach to examine resting-state directional information flow networks, quantified by phase-transfer entropy (PTE), in patients with TLE compared with healthy controls (HCs). Associations between PTE and clinical characteristics of epilepsy syndrome are also investigated. Results: Deficits of information flow were specific to alpha-band frequencies. In alpha band, while HCs exhibit a clear posterior-to-anterior directionality of information flow, in patients with TLE, this pattern of regional information outflow and inflow was significantly altered in the frontal and occipital regions. The changes in information flow within the alpha band in selected brain regions were correlated with interictal spike frequency and duration of epilepsy. Conclusions: Impaired information flow is an important dimension of network dysfunction associated with the pathophysiological mechanisms of TLE.

Background: Neuronal- and circuit-level abnormalities of excitation and inhibition are shown to be associated with tau and amyloid-beta (Aβ) in preclinical models of Alzheimer’s disease (AD). These relationships remain poorly understood in patients with AD. Methods: Using empirical spectra from magnetoencephalography and computational modeling (neural mass model), we examined excitatory and inhibitory parameters of neuronal subpopulations and investigated their specific associations to regional tau and Aβ, measured by positron emission tomography, in patients with AD. Results: Patients with AD showed abnormal excitatory and inhibitory time-constants and neural gains compared to age-matched controls. Increased excitatory time-constants distinctly correlated with higher tau depositions while increased inhibitory time-constants distinctly correlated with higher Aβ depositions. Conclusions: Our results provide critical insights about potential mechanistic links between abnormal neural oscillations and cellular correlates of impaired excitatory and inhibitory synaptic functions associated with tau and Aβ in patients with AD. Funding: This study was supported by the National Institutes of Health grants: K08AG058749 (KGR), F32AG050434-01A1 (KGR), K23 AG038357 (KAV), P50 AG023501, P01 AG19724 (BLM), P50-AG023501 (BLM and GDR), R01 AG045611 (GDR); AG034570, AG062542 (WJ); NS100440 (SSN), DC176960 (SSN), DC017091 (SSN), AG062196 (SSN); a grant from John Douglas French Alzheimer’s Foundation (KAV); grants from Larry L. Hillblom Foundation: 2015-A-034-FEL (KGR), 2019-A-013-SUP (KGR); grants from the Alzheimer’s Association: AARG-21-849773 (KGR); PCTRB-13-288476 (KAV), and made possible by Part the CloudTM (ETAC-09-133596); a grant from Tau Consortium (GDR and WJJ), and a gift from the S. D. Bechtel Jr. Foundation.

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.

Since the first demonstrations of network hyperexcitability in scientific models of Alzheimer's disease, a growing body of clinical studies have identified subclinical epileptiform activity and associated cognitive decline in patients with Alzheimer's disease. An obvious problem presented in these studies is lack of sensitive measures to detect and quantify network hyperexcitability in human subjects. In this study we examined whether altered neuronal synchrony can be a surrogate marker to quantify network hyperexcitability in patients with Alzheimer's disease. Using magnetoencephalography (MEG) at rest, we studied 30 Alzheimer's disease patients without subclinical epileptiform activity, 20 Alzheimer's disease patients with subclinical epileptiform activity and 35 age-matched controls. Presence of subclinical epileptiform activity was assessed in patients with Alzheimer's disease by long-term video-EEG and a 1-h resting MEG with simultaneous EEG. Using the resting-state source-space reconstructed MEG signal, in patients and controls we computed the global imaginary coherence in alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillatory frequencies. We found that Alzheimer's disease patients with subclinical epileptiform activity have greater reductions in alpha imaginary coherence and greater enhancements in delta-theta imaginary coherence than Alzheimer's disease patients without subclinical epileptiform activity, and that these changes can distinguish between Alzheimer's disease patients with subclinical epileptiform activity and Alzheimer's disease patients without subclinical epileptiform activity with high accuracy. Finally, a principal component regression analysis showed that the variance of frequency-specific neuronal synchrony predicts longitudinal changes in Mini-Mental State Examination in patients and controls. Our results demonstrate that quantitative neurophysiological measures are sensitive biomarkers of network hyperexcitability and can be used to improve diagnosis and to select appropriate patients for the right therapy in the next-generation clinical trials. The current results provide an integrative framework for investigating network hyperexcitability and network dysfunction together with cognitive and clinical correlates in patients with Alzheimer's disease.

Oscillatory brain rhythms are a defining feature of neuronal activity that support cognition in humans. Previous studies that showed associations of spectral changes in individuals who harbor high risk for Alzheimer’s disease (AD) were limited to identify abnormalities within select brain regions defined apriori. Comprehensive whole-brain spatiotemporal patterns of oscillatory changes associated with cognitive-aging and with AD risk are only partly known. Our main goals were to understand how frequency specific spectral changes relate to cognitive abilities in normal aging and to identify oscillatory signatures that indicate pre-symptomatic AD pathophysiological processes in cognitively unimpaired elderly. We used magnetoencephalography (MEG) to study the spectral signatures within delta-theta (2-7Hz), alpha (8-12Hz) and beta (13-35Hz) oscillations, in cognitively unimpaired adults (n=70). Using a partial-least-square regression, we correlated spectral patterns to executive, memory, and processing-speed abilities (n=40). Next, we compared the spectral signatures between amyloid-β (Aβ)+ vs. Aβ- and between APOE-Ɛ4+ vs. APOE-Ɛ4-, in sub-cohorts evaluated with Aβ-PET (n=46) and APOE4 (n=65), respectively. In a subset of participants (n=19), we also examined associations between spectral signatures and cerebrospinal fluid (CSF) markers indicating damage to: presynaptic (growth-associated protein-43, GAP43); postsynaptic (neurogranin, NG); axonal (neurofilament light chain, NFL), levels. An age dependent, low-grade, increase in alpha power and decrease in delta-theta power were associated with better cognitive performance in memory, executive and processing speed (Figure-1). APOE4+ individuals showed reduced alpha power within bilateral medial temporal and right precuneus, compared to APOE4-. Aβ+ individuals showed a dual pattern of alpha change with increased frontal and reduced medial and lateral temporal cortex pattern and a frontally distributed increased delta-theta power (Figure-2). Higher CSF-NFL was correlated with lower alpha power. Our findings demonstrate that higher alpha power indicates a positive spectral change towards better cognitive health in aging. Importantly, a reduced alpha power signature indicated early neurodegenerative changes, as demonstrated by: (1)Aβ+ individuals and APOE-Ɛ4+ individuals showing reduced alpha power within the regions known for earliest tau accumulations; (2) lower alpha correlating with higher NFL, which reflects Aβ-independent neurodegeneration. Collectively alpha signatures may indicate tau related neuropathology with aging and in early AD.

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.

1Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158 2Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA 94143 3Medical Imaging Business Center, Ricoh Company, Ltd., Kanazawa 920-0177, Japan 4Helen Wills Neuroscience Institute, UC Berkeley, Berkeley, CA 94720 5Mary S. Easton Center for Alzheimer’s Disease Research, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095

n amendment to this paper has been published and can be accessed via a link at the top of the paper.