Abnormal gamma phase-amplitude coupling in the parahippocampal cortex is associated with network hyperexcitability in Alzheimer's disease.

While animal models of Alzheimer's disease (AD) have shown altered gamma oscillations (∼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.

Neurophysiological trajectories in Alzheimer's disease progression.

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-ß and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. The increases in neural synchrony in the delta-theta band and the decreases in the alpha and beta bands showed progressive changes throughout the stages of the EBM. Decreases in alpha and beta band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.

Global MEG Resting State Functional Connectivity in Children with Autism and Sensory Processing Dysfunction.

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.

Spatiotemporal characteristics of neurophysiological changes in patients with four-repeat tauopathies.

INTRODUCTION: Progressive supranuclear palsy (PSP) and corticobasal degeneration (CBD), are the most common four-repeat tauopathies (4RT), and both frequently occur with varying degree of Alzheimer's disease (AD) copathology. Intriguingly, patients with 4RT and patients with AD are at opposite ends of the wakefulness spectrum-AD showing reduced wakefulness and excessive sleepiness whereas 4RT showing decreased homeostatic sleep. The neural mechanisms underlying these distinct phenotypes in the comorbid condition of 4RT and AD are unknown. The objective of the current study was to define the alpha oscillatory spectrum, which is prominent in the awake resting-state in the human brain, in patients with primary 4RT, and how it is modified in comorbid AD-pathology. METHOD: In an autopsy-confirmed case series of 4R-tauopathy patients (n = 10), whose primary neuropathological diagnosis was either PSP (n = 7) or CBD (n = 3), using high spatiotemporal resolution magnetoencephalography (MEG), we quantified the spectral power density within alpha-band (8-12 Hz) and examined how this pattern was modified in increasing AD-copathology. For each patient, their regional alpha power was compared to an age-matched normative control cohort (n = 35). RESULT: Patients with 4RT showed increased alpha power but in the presence of AD-copathology alpha power was reduced. CONCLUSIONS: Alpha power increase in PSP-tauopathy and reduction in the presence of AD-tauopathy is consistent with the observation that neurons activating wakefulness-promoting systems are preserved in PSP but degenerated in AD. These results highlight the selectively vulnerable impacts in 4RT versus AD-tauopathy that may have translational significance on disease-modifying therapies for specific proteinopathies.

Neurophysiological trajectories in Alzheimer's disease progression.

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-ß and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. The increases in neural synchrony in the delta-theta band and the decreases in the alpha and beta bands showed progressive changes throughout the stages of the EBM. Decreases in alpha and beta band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.

Cortical Synchrony and Information Flow during Transition from Wakefulness to Light Non-Rapid Eye Movement Sleep.

Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.

Dynamic functional connectivity MEG features of Alzheimer's disease.

Dynamic resting state functional connectivity (RSFC) characterizes time-varying fluctuations of functional brain network activity. While many studies have investigated static functional connectivity, it has been unclear whether features of dynamic functional connectivity are associated with neurodegenerative diseases. Popular sliding-window and clustering methods for extracting dynamic RSFC have various limitations that prevent extracting reliable features to address this question. Here, we use a novel and robust time-varying dynamic network (TVDN) approach to extract the dynamic RSFC features from high resolution magnetoencephalography (MEG) data of participants with Alzheimer's disease (AD) and matched controls. The TVDN algorithm automatically and adaptively learns the low-dimensional spatiotemporal manifold of dynamic RSFC and detects dynamic state transitions in data. We show that amongst all the functional features we investigated, the dynamic manifold features are the most predictive of AD. These include: the temporal complexity of the brain network, given by the number of state transitions and their dwell times, and the spatial complexity of the brain network, given by the number of eigenmodes. These dynamic features have higher sensitivity and specificity in distinguishing AD from healthy subjects than the existing benchmarks do. Intriguingly, we found that AD patients generally have higher spatial complexity but lower temporal complexity compared with healthy controls. We also show that graph theoretic metrics of dynamic component of TVDN are significantly different in AD versus controls, while static graph metrics are not statistically different. These results indicate that dynamic RSFC features are impacted in neurodegenerative disease like Alzheimer's disease, and may be crucial to understanding the pathophysiological trajectory of these diseases.

Impaired Speaking-Induced Suppression in Alzheimer's Disease.

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.

Functional neuronal circuitry and oscillatory dynamics in human brain organoids.

Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiology of neuronal circuits within organoids remains under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we captured spontaneous extracellular activity from brain organoids derived from human induced pluripotent stem cells. We inferred functional connectivity from spike timing, revealing a large number of weak connections within a skeleton of significantly fewer strong connections. A benzodiazepine increased the uniformity of firing patterns and decreased the relative fraction of weakly connected edges. Our analysis of the local field potential demonstrate that brain organoids contain neuronal assemblies of sufficient size and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug action, and the effects of external stimuli upon neuronal networks.

Altered excitatory and inhibitory neuronal subpopulation parameters are distinctly associated with tau and amyloid in Alzheimer's disease.

Background: Neuronal- and circuit-level abnormalities of excitation and inhibition are shown to be associated with tau and amyloid-beta (Aß) 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 Aß, 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 Aß 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 Aß 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.

Network connectivity predicts effectiveness of responsive neurostimulation in focal epilepsy.

Responsive neurostimulation is a promising treatment for drug-resistant focal epilepsy; however, clinical outcomes are highly variable across individuals. The therapeutic mechanism of responsive neurostimulation likely involves modulatory effects on brain networks; however, with no known biomarkers that predict clinical response, patient selection remains empiric. This study aimed to determine whether functional brain connectivity measured non-invasively prior to device implantation predicts clinical response to responsive neurostimulation therapy. Resting-state magnetoencephalography was obtained in 31 participants with subsequent responsive neurostimulation device implantation between 15 August 2014 and 1 October 2020. Functional connectivity was computed across multiple spatial scales (global, hemispheric, and lobar) using pre-implantation magnetoencephalography and normalized to maps of healthy controls. Normalized functional connectivity was investigated as a predictor of clinical response, defined as percent change in self-reported seizure frequency in the most recent year of clinic visits relative to pre-responsive neurostimulation baseline. Area under the receiver operating characteristic curve quantified the performance of functional connectivity in predicting responders (≥50% reduction in seizure frequency) and non-responders (<50%). Leave-one-out cross-validation was furthermore performed to characterize model performance. The relationship between seizure frequency reduction and frequency-specific functional connectivity was further assessed as a continuous measure. Across participants, stimulation was enabled for a median duration of 52.2 (interquartile range, 27.0-62.3) months. Demographics, seizure characteristics, and responsive neurostimulation lead configurations were matched across 22 responders and 9 non-responders. Global functional connectivity in the alpha and beta bands were lower in non-responders as compared with responders (alpha, pfdr < 0.001; beta, pfdr < 0.001). The classification of responsive neurostimulation outcome was improved by combining feature inputs; the best model incorporated four features (i.e. mean and dispersion of alpha and beta bands) and yielded an area under the receiver operating characteristic curve of 0.970 (0.919-1.00). The leave-one-out cross-validation analysis of this four-feature model yielded a sensitivity of 86.3%, specificity of 77.8%, positive predictive value of 90.5%, and negative predictive value of 70%. Global functional connectivity in alpha band correlated with seizure frequency reduction (alpha, P = 0.010). Global functional connectivity predicted responder status more strongly, as compared with hemispheric predictors. Lobar functional connectivity was not a predictor. These findings suggest that non-invasive functional connectivity may be a candidate personalized biomarker that has the potential to predict responsive neurostimulation effectiveness and to identify patients most likely to benefit from responsive neurostimulation therapy. Follow-up large-cohort, prospective studies are required to validate this biomarker. These findings furthermore support an emerging view that the therapeutic mechanism of responsive neurostimulation involves network-level effects in the brain.

Magnetoencephalography Imaging Reveals Abnormal Information Flow in Temporal Lobe Epilepsy.

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.

Neuronal synchrony abnormalities associated with subclinical epileptiform activity in early-onset Alzheimer's disease.

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.

Effect of Levetiracetam on Cognition in Patients With Alzheimer Disease With and Without Epileptiform Activity: A Randomized Clinical Trial.

Importance: Network hyperexcitability may contribute to cognitive dysfunction in patients with Alzheimer disease (AD). Objective: To determine the ability of the antiseizure drug levetiracetam to improve cognition in persons with AD. Design, Setting, and Participants: The Levetiracetam for Alzheimer's Disease-Associated Network Hyperexcitability (LEV-AD) study was a phase 2a randomized double-blinded placebo-controlled crossover clinical trial of 34 adults with AD that was conducted at the University of California, San Francisco, and the University of Minnesota, Twin Cities, between October 16, 2014, and July 21, 2020. Participants were adults 80 years and younger who had a Mini-Mental State Examination score of 18 points or higher and/or a Clinical Dementia Rating score of less than 2 points. Screening included overnight video electroencephalography and a 1-hour resting magnetoencephalography examination. Interventions: Group A received placebo twice daily for 4 weeks followed by a 4-week washout period, then oral levetiracetam, 125 mg, twice daily for 4 weeks. Group B received treatment using the reverse sequence. Main Outcomes and Measures: The primary outcome was the ability of levetiracetam treatment to improve executive function (measured by the National Institutes of Health Executive Abilities: Measures and Instruments for Neurobehavioral Evaluation and Research [NIH-EXAMINER] composite score). Secondary outcomes were cognition (measured by the Stroop Color and Word Test [Stroop] interference naming subscale and the Alzheimer's Disease Assessment Scale-Cognitive Subscale) and disability. Exploratory outcomes included performance on a virtual route learning test and scores on cognitive and functional tests among participants with epileptiform activity. Results: Of 54 adults assessed for eligibility, 11 did not meet study criteria, and 9 declined to participate. A total of 34 adults (21 women [61.8%]; mean [SD] age, 62.3 [7.7] years) with AD were enrolled and randomized (17 participants to group A and 17 participants to group B). Thirteen participants (38.2%) were categorized as having epileptiform activity. In total, 28 participants (82.4%) completed the study, 10 of whom (35.7%) had epileptiform activity. Overall, treatment with levetiracetam did not change NIH-EXAMINER composite scores (mean difference vs placebo, 0.07 points; 95% CI, -0.18 to 0.32 points; P = .55) or secondary measures. However, among participants with epileptiform activity, levetiracetam treatment improved performance on the Stroop interference naming subscale (net improvement vs placebo, 7.4 points; 95% CI, 0.2-14.7 points; P = .046) and the virtual route learning test (t = 2.36; Cohen f2 = 0.11; P = .02). There were no treatment discontinuations because of adverse events. Conclusions and Relevance: In this randomized clinical trial, levetiracetam was well tolerated and, although it did not improve the primary outcome, in prespecified analysis, levetiracetam improved performance on spatial memory and executive function tasks in patients with AD and epileptiform activity. These exploratory findings warrant further assessment of antiseizure approaches in AD. Trial Registration: ClinicalTrials.gov Identifier: NCT02002819.

Computationally derived anatomic subtypes of behavioral variant frontotemporal dementia show temporal stability and divergent patterns of longitudinal atrophy.

INTRODUCTION: Behavioral variant frontotemporal dementia (bvFTD) can be computationally divided into four distinct anatomic subtypes based on patterns of frontotemporal and subcortical atrophy. To more precisely predict disease trajectories of individual patients, the temporal stability of each subtype must be characterized. METHODS: We investigated the longitudinal stability of the four previously identified anatomic subtypes in 72 bvFTD patients. We also applied a voxel-wise mixed effects model to examine subtype differences in atrophy patterns across multiple timepoints. RESULTS: Our results demonstrate the stability of the anatomic subtypes at baseline and over time. While they had common salience network atrophy, each subtype showed distinctive baseline and longitudinal atrophy patterns. DISCUSSION: Recognizing these anatomically heterogeneous subtypes and their different patterns of atrophy progression in early bvFTD will improve disease course prediction in individual patients. Longitudinal volumetric predictions based on these anatomic subtypes may be used as a more accurate endpoint in treatment trials.

Reduced synchrony in alpha oscillations during life predicts post mortem neurofibrillary tangle density in early-onset and atypical Alzheimer's disease.

INTRODUCTION: Neurophysiological manifestations selectively associated with amyloid beta and tau depositions in Alzheimer's disease (AD) are useful network biomarkers to identify peptide specific pathological processes. The objective of this study was to validate the associations between reduced neuronal synchrony within alpha oscillations and neurofibrillary tangle (NFT) density in autopsy examination, in patients with AD. METHODS: In a well-characterized clinicopathological cohort of AD patients (n = 13), we quantified neuronal synchrony within alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillations, using magnetoencephalography during the disease course, within six selected neocortical and hippocampal regions, including angular gyrus, superior temporal gurus, middle frontal gyrus, primary motor cortex, CA1, and subiculum, and correlated these with regional NFT density quantified at histopathological examination. RESULTS: Abnormal synchrony in alpha, but not in delta-theta, significantly predicted the NFT density at post mortem neuropathological examination. DISCUSSION: Reduced alpha synchrony is a sensitive neurophysiological index associated with pathological tau, and a potential network biomarker for clinical trials, to gauge the extent of network dysfunction and the degree of rescue in treatments targeting tau pathways in AD.

Taking the sublexical route: brain dynamics of reading in the semantic variant of primary progressive aphasia.

Reading aloud requires mapping an orthographic form to a phonological one. The mapping process relies on sublexical statistical regularities (e.g. 'oo' to |uː|) or on learned lexical associations between a specific visual form and a series of sounds (e.g. yacht to/jɑt/). Computational, neuroimaging, and neuropsychological evidence suggest that sublexical, phonological and lexico-semantic processes rely on partially distinct neural substrates: a dorsal (occipito-parietal) and a ventral (occipito-temporal) route, respectively. Here, we investigated the spatiotemporal features of orthography-to-phonology mapping, capitalizing on the time resolution of magnetoencephalography and the unique clinical model offered by patients with semantic variant of primary progressive aphasia (svPPA). Behaviourally, patients with svPPA manifest marked lexico-semantic impairments including difficulties in reading words with exceptional orthographic to phonological correspondence (irregular words). Moreover, they present with focal neurodegeneration in the anterior temporal lobe, affecting primarily the ventral, occipito-temporal, lexical route. Therefore, this clinical population allows for testing of specific hypotheses on the neural implementation of the dual-route model for reading, such as whether damage to one route can be compensated by over-reliance on the other. To this end, we reconstructed and analysed time-resolved whole-brain activity in 12 svPPA patients and 12 healthy age-matched control subjects while reading irregular words (e.g. yacht) and pseudowords (e.g. pook). Consistent with previous findings that the dorsal route is involved in sublexical, phonological processes, in control participants we observed enhanced neural activity over dorsal occipito-parietal cortices for pseudowords, when compared to irregular words. This activation was manifested in the beta-band (12-30 Hz), ramping up slowly over 500 ms after stimulus onset and peaking at ∼800 ms, around response selection and production. Consistent with our prediction, svPPA patients did not exhibit this temporal pattern of neural activity observed in controls this contrast. Furthermore, a direct comparison of neural activity between patients and controls revealed a dorsal spatiotemporal cluster during irregular word reading. These findings suggest that the sublexical/phonological route is involved in processing both irregular and pseudowords in svPPA. Together these results provide further evidence supporting a dual-route model for reading aloud mediated by the interplay between lexico-semantic and sublexical/phonological neurocognitive systems. When the ventral route is damaged, as in the case of neurodegeneration affecting the anterior temporal lobe, partial compensation appears to be possible by over-recruitment of the slower, serial attention-dependent, dorsal one.

Depressive Symptom Profiles Predict Specific Neurodegenerative Disease Syndromes in Early Stages.

Background: During early stages, patients with neurodegenerative diseases (NDG) often present with depressive symptoms. However, because depression is a heterogeneous disorder, more precise delineation of the specific depressive symptom profiles that arise early in distinct NDG syndromes is necessary to enhance patient diagnosis and care. Methods and Findings: Five-hundred and sixty four participants self-reported their depressive symptoms using the Geriatric Depression Scale (GDS), including 111 healthy older control subjects (NC) and 453 patients diagnosed with one of six NDGs who were at the mild stage of disease (CDR® Dementia Staging Instrument ≤ 1) [186 Alzheimer's disease (AD), 76 behavioral variant frontotemporal dementia (bvFTD), 52 semantic variant primary progressive aphasia (svPPA), 46 non-fluent variant PPA (nfvPPA), 49 progressive supranuclear palsy syndrome (PSPS), 44 corticobasal syndrome (CBS)]. The GDS was divided into subscales based on a previously published factor analysis, representing five symptoms (dysphoria, hopelessness, withdrawal, worry, and cognitive concerns). Mixed models were created to examine differences in depression subscale by group, and logistic regression analyses were performed to determine if patterns of depressive symptoms could predict a patient's NDG syndrome. PSPS patients presented with a hopeless, dysphoric, and withdrawn pattern, while patients with CBS presented with a similar but less severe pattern. Worry was a key symptom in the profile of patients with svPPA, while ADs only had abnormally elevated cognitive concerns. Depressive profile accurately predicted NDG diagnosis at a rate of between 70 and 84% accuracy. Conclusions: These results suggest that attention to specific depressive symptom profile can improve diagnostic sensitivity and can be used to provide more individualized patient care.

Global resting-state functional connectivity of neural oscillations in tinnitus with and without hearing loss.

This study examined global resting-state functional connectivity of neural oscillations in individuals with chronic tinnitus and normal and impaired hearing. We tested the hypothesis that distinct neural oscillatory networks are engaged in tinnitus with and without hearing loss. In both tinnitus groups, with and without hearing loss, we identified multiple frequency band-dependent regions of increased and decreased global functional connectivity. We also found that the auditory domain of tinnitus severity, assayed by the Tinnitus Functional Index, was associated with global functional connectivity in both auditory and nonauditory regions. These findings provide candidate biomarkers to target and monitor treatments for tinnitus with and without hearing loss.

Neurophysiological signatures in Alzheimer's disease are distinctly associated with TAU, amyloid-ß accumulation, and cognitive decline.

Neural synchrony is intricately balanced in the normal resting brain but becomes altered in Alzheimer's disease (AD). To determine the neurophysiological manifestations associated with molecular biomarkers of AD neuropathology, in patients with AD, we used magnetoencephalographic imaging (MEGI) and positron emission tomography with amyloid-beta (Aß) and TAU tracers. We found that alpha oscillations (8 to 12 Hz) were hyposynchronous in occipital and posterior temporoparietal cortices, whereas delta-theta oscillations (2 to 8 Hz) were hypersynchronous in frontal and anterior temporoparietal cortices, in patients with AD compared to age-matched controls. Regional patterns of alpha hyposynchrony were unique in each neurobehavioral phenotype of AD, whereas the regional patterns of delta-theta hypersynchrony were similar across the phenotypes. Alpha hyposynchrony strongly colocalized with TAU deposition and was modulated by the degree of TAU tracer uptake. In contrast, delta-theta hypersynchrony colocalized with both TAU and Aß depositions and was modulated by both TAU and Aß tracer uptake. Furthermore, alpha hyposynchrony but not delta-theta hypersynchrony was correlated with the degree of global cognitive dysfunction in patients with AD. The current study demonstrates frequency-specific neurophysiological signatures of AD pathophysiology and suggests that neurophysiological measures from MEGI are sensitive indices of network disruptions mediated by TAU and Aß and associated cognitive decline. These findings facilitate the pursuit of novel therapeutic approaches toward normalizing network synchrony in AD.