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.

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.

Clinical Validation of the Champagne Algorithm for Evoked Response Source Localization in Magnetoencephalography.

Magnetoencephalography (MEG) is a robust method for non-invasive functional brain mapping of sensory cortices due to its exceptional spatial and temporal resolution. The clinical standard for MEG source localization of functional landmarks from sensory evoked responses is the equivalent current dipole (ECD) localization algorithm, known to be sensitive to initialization, noise, and manual choice of the number of dipoles. Recently many automated and robust algorithms have been developed, including the Champagne algorithm, an empirical Bayesian algorithm, with powerful abilities for MEG source reconstruction and time course estimation (Wipf et al. 2010; Owen et al. 2012). Here, we evaluate automated Champagne performance in a clinical population of tumor patients where there was minimal failure in localizing sensory evoked responses using the clinical standard, ECD localization algorithm. MEG data of auditory evoked potentials and somatosensory evoked potentials from 21 brain tumor patients were analyzed using Champagne, and these results were compared with equivalent current dipole (ECD) fit. Across both somatosensory and auditory evoked field localization, we found there was a strong agreement between Champagne and ECD localizations in all cases. Given resolution of 8mm voxel size, peak source localizations from Champagne were below 10mm of ECD peak source localization. The Champagne algorithm provides a robust and automated alternative to manual ECD fits for clinical localization of sensory evoked potentials and can contribute to improved clinical MEG data processing workflows.

What Is Different about Teratoma-Associated Anti-LGI1 Encephalitis? A Long-Term Clinical and Neuroimaging Case Series.

INTRODUCTION: Anti-leucine-rich glioma-inactivated 1 (LGI1) encephalitis is clinically heterogeneous, especially at presentation, and though it is sometimes found in association with tumor, this is by no means the rule. METHODS: Clinical data for 10 patients with anti-LGI1 encephalitis were collected including one case with teratoma and nine cases without and compared for clinical characteristics. Microscopic pathological examination and immunohistochemical assay of the LGI1 antibody were performed on teratoma tissue obtained by laparoscopic oophorocystectomy. RESULTS: In our teratoma-associated anti-LGI1 encephalitis case, teratoma pathology was characterized by mostly thyroid tissue and immunohistochemical assay confirmed positive nuclear staining of LGI1 in some tumor cells. The anti-LGl1 patient with teratoma was similar to the non-teratoma cases in many ways: age at onset (average 47.3 in non-teratoma cases); percent presenting with rapidly progressive dementia (67% of non-teratoma cases) and psychiatric symptoms (33%); hyponatremia (78%); normal cerebrospinal fluid results except for positive LGI1 antibody (78%); bilateral hippocampal hyperintensity on magnetic resonance imaging (44%); diffuse slow waves on electroencephalography (33%); good response to immunotherapy (67%); and mild residual cognitive deficit (22%). Her chronic anxiety and presentation with status epilepticus were the biggest differences compared with the non-teratoma cases. CONCLUSION: In our series, anti-LGI1 encephalitis included common clinical features in our series: rapidly progressive dementia, faciobrachial dystonic seizures, behavioral disorders, hyponatremia, hippocampal hyperintensity on magnetic resonance imaging, and residual cognitive deficit. We observed some differences (chronic anxiety and status epilepticus) in our case with teratoma, but a larger accumulation of cases is needed to improve our knowledge base.

"What is the mechanism?": Cues, barriers, and opportunities to discuss foundational science during internal medicine rounds.

BACKGROUND: Repeated application of foundational science (FS) during medical reasoning results in encapsulation of knowledge needed to develop clinical expertise. Despite proven benefit of educating learners using a FS framework to anchor clinical decision making, how FS is integrated on clinical rotations has not been well characterized. This study examines how and when FS discussion occurs on internal medicine teaching rounds. MATERIAL AND METHODS: We performed a convergent mixed method study. Six internal medicine teams at a quaternary hospital were observed during rounds and team members interviewed. Transcripts were analyzed using thematic analysis. Descriptive statistics provided a summary of the observations. RESULTS: Our study revealed that rounds used a teacher-centered model where FS knowledge was transmitted as pearls external to the clinical context. FS content arose primarily when the patient was complex. Barriers preventing FS discussion were lack of time and perceived lack of personal FS knowledge. CONCLUSION: Our study describes scenarios that commonly elicit discussion of FS on inpatient medicine rounds highlighting a 'transmission' model of FS knowledge. We suggest a learner-centered model that engages students in the practice of integrating FS into clinical reasoning.

Integrated in silico and experimental assessment of disease relevance of PCDH19 missense variants.

PCDH19 is a nonclustered protocadherin molecule involved in axon bundling, synapse function, and transcriptional coregulation. Pathogenic variants in PCDH19 cause infantile-onset epilepsy known as PCDH19-clustering epilepsy or PCDH19-CE. Recent advances in DNA-sequencing technologies have led to a significant increase in the number of reported PCDH19-CE variants, many of uncertain significance. We aimed to determine the best approaches for assessing the disease relevance of missense variants in PCDH19. The application of the American College of Medical Genetics and Association for Molecular Pathology (ACMG-AMP) guidelines was only 50% accurate. Using a training set of 322 known benign or pathogenic missense variants, we identified MutPred2, MutationAssessor, and GPP as the best performing in silico tools. We generated a protein structural model of the extracellular domain and assessed 24 missense variants. We also assessed 24 variants using an in vitro reporter assay. A combination of these tools was 93% accurate in assessing known pathogenic and benign PCDH19 variants. We increased the accuracy of the ACMG-AMP classification of 45 PCDH19 variants from 50% to 94%, using these tools. In summary, we have developed a robust toolbox for the assessment of PCDH19 variant pathogenicity to improve the accuracy of PCDH19-CE variant classification.

Long QT syndrome with potassium voltage-gated channel subfamily H member 2 gene mutation mimicking refractory epilepsy: case report.

BACKGROUND: Epileptic seizures can be difficult to distinguish from other etiologies that cause cerebral hypoxia, especially cardiac diseases. Long QT syndrome (LQTS), especially LQTS type 2 (LQT2), frequently masquerades as seizures because of the transient cerebral hypoxia caused by ventricular arrhythmia. The high rate of sudden death in LQTS highlights the importance of accurate and early diagnosis; correct diagnosis of LQTS also prevents inappropriate treatment with anti-epileptic drugs (AEDs). CASE PRESENTATION: We report a case of congenital LQT2 with potassium voltage-gated channel subfamily H member 2 gene (KCNH2) mutation misdiagnosed as refractory epilepsy and treated with various AEDs for 22 years. The possibility of cardiac arrhythmia was suspected after the patient presented to the emergency room and the electrocardiograph (ECG) monitor showed paroxysmal ventricular tachycardia during attacks. Atypical seizure like attacks with prodromal uncomfortable chest sensation and palpitation, triggered by auditory stimulation, and typical ventricular tachycardia monitored by ECG raised suspicion for LQT2, which was confirmed by exome sequencing and epileptic seizure was ruled out by 24-h EEG monitoring. Although the patient rejected implantation of an implantable cardioverter defibrillator, ß blocker was given and the syncope only attacked 1-2 per year when there was an incentive during the 5 years follow up. CONCLUSIONS: Our case illustrates how long LQTS can masquerade convincingly as epilepsy and can be treated wrongly with AEDs, putting the patient at high risk of sudden cardiac death. Careful ECG evaluation is recommend for both patients with first seizure and those with refractory epilepsy.

Direct Evidence for Prediction Signals in Frontal Cortex Independent of Prediction Error.

Predictive coding (PC) has been suggested as one of the main mechanisms used by brains to interact with complex environments. PC theories posit top-down prediction signals, which are compared with actual outcomes, yielding in turn prediction error (PE) signals, which are used, bottom-up, to modify the ensuing predictions. However, disentangling prediction from PE signals has been challenging. Critically, while many studies found indirect evidence for PC in the form of PE signals, direct evidence for the prediction signal is mostly lacking. Here, we provide clear evidence, obtained from intracranial cortical recordings in human surgical patients, that the human lateral prefrontal cortex evinces prediction signals while anticipating an event. Patients listened to task-irrelevant sequences of repetitive tones including infrequent predictable or unpredictable pitch deviants. The broadband high-frequency amplitude (HFA) was decreased prior to the onset of expected relative to unexpected deviants in the frontal cortex only, and its amplitude was sensitive to the increasing likelihood of deviants following longer trains of standards in the unpredictable condition. Single-trial HFA predicted deviations and correlated with poststimulus response to deviations. These results provide direct evidence for frontal cortex prediction signals independent of PE signals.

Evaluation of a dual signal subspace projection algorithm in magnetoencephalographic recordings from patients with intractable epilepsy and vagus nerve stimulators.

Magnetoencephalography (MEG) data is subject to many sources of environmental noise, and interference rejection is a necessary step in the processing of MEG data. Large amplitude interference caused by sources near the brain have been common in clinical settings and are difficult to reject. Artifact from vagal nerve stimulators (VNS) is a prototypical example. In this study, we describe a novel MEG interference rejection algorithm called dual signal subspace projection (DSSP), and evaluate its performance in clinical MEG data from people with epilepsy and implanted VNS. The performance of DSSP was evaluated in a retrospective cohort study of patients with epilepsy and VNS who had MEG scans for source localization of interictal epileptiform discharges. DSSP was applied to the MEG data and compared with benchmark for performance. We evaluated the clinical impact of interference rejection based on human expert detection and estimation of the location and time-course of interictal spikes, using an empirical Bayesian source reconstruction algorithm (Champagne). Clinical recordings, after DSSP processing, became more readable and a greater number of interictal epileptic spikes could be clearly identified. Source localization results of interictal spikes also significantly improved from those achieved before DSSP processing, including meaningful estimates of activity time courses. Therefore, DSSP is a valuable novel interference rejection algorithm that can be successfully deployed for the removal of strong artifacts and interferences in MEG.

Hierarchy of prediction errors for auditory events in human temporal and frontal cortex.

Predictive coding theories posit that neural networks learn statistical regularities in the environment for comparison with actual outcomes, signaling a prediction error (PE) when sensory deviation occurs. PE studies in audition have capitalized on low-frequency event-related potentials (LF-ERPs), such as the mismatch negativity. However, local cortical activity is well-indexed by higher-frequency bands [high-γ band (Hγ): 80-150 Hz]. We compared patterns of human Hγ and LF-ERPs in deviance detection using electrocorticographic recordings from subdural electrodes over frontal and temporal cortices. Patients listened to trains of task-irrelevant tones in two conditions differing in the predictability of a deviation from repetitive background stimuli (fully predictable vs. unpredictable deviants). We found deviance-related responses in both frequency bands over lateral temporal and inferior frontal cortex, with an earlier latency for Hγ than for LF-ERPs. Critically, frontal Hγ activity but not LF-ERPs discriminated between fully predictable and unpredictable changes, with frontal cortex sensitive to unpredictable events. The results highlight the role of frontal cortex and Hγ activity in deviance detection and PE generation.

Incidence and impact of subclinical epileptiform activity in Alzheimer's disease.

OBJECTIVE: Seizures are more frequent in patients with Alzheimer's disease (AD) and can hasten cognitive decline. However, the incidence of subclinical epileptiform activity in AD and its consequences are unknown. Motivated by results from animal studies, we hypothesized higher than expected rates of subclinical epileptiform activity in AD with deleterious effects on cognition. METHODS: We prospectively enrolled 33 patients (mean age, 62 years) who met criteria for AD, but had no history of seizures, and 19 age-matched, cognitively normal controls. Subclinical epileptiform activity was assessed, blinded to diagnosis, by overnight long-term video-electroencephalography (EEG) and a 1-hour resting magnetoencephalography exam with simultaneous EEG. Patients also had comprehensive clinical and cognitive evaluations, assessed longitudinally over an average period of 3.3 years. RESULTS: Subclinical epileptiform activity was detected in 42.4% of AD patients and 10.5% of controls (p = 0.02). At the time of monitoring, AD patients with epileptiform activity did not differ clinically from those without such activity. However, patients with subclinical epileptiform activity showed faster declines in global cognition, determined by the Mini-Mental State Examination (3.9 points/year in patients with epileptiform activity vs 1.6 points/year in patients without; p = 0.006), and in executive function (p = 0.01). INTERPRETATION: Extended monitoring detects subclinical epileptiform activity in a substantial proportion of patients with AD. Patients with this indicator of network hyperexcitability are at risk for accelerated cognitive decline and might benefit from antiepileptic therapies. These data call for more sensitive and comprehensive neurophysiological assessments in AD patient evaluations and impending clinical trials. Ann Neurol 2016;80:858-870.

Global and regional functional connectivity maps of neural oscillations in focal epilepsy.

Intractable focal epilepsy is a devastating disorder with profound effects on cognition and quality of life. Epilepsy surgery can lead to seizure freedom in patients with focal epilepsy; however, sometimes it fails due to an incomplete delineation of the epileptogenic zone. Brain networks in epilepsy can be studied with resting-state functional connectivity analysis, yet previous investigations using functional magnetic resonance imaging or electrocorticography have produced inconsistent results. Magnetoencephalography allows non-invasive whole-brain recordings, and can be used to study both long-range network disturbances in focal epilepsy and regional connectivity at the epileptogenic zone. In magnetoencephalography recordings from presurgical epilepsy patients, we examined: (i) global functional connectivity maps in patients versus controls; and (ii) regional functional connectivity maps at the region of resection, compared to the homotopic non-epileptogenic region in the contralateral hemisphere. Sixty-one patients were studied, including 30 with mesial temporal lobe epilepsy and 31 with focal neocortical epilepsy. Compared with a group of 31 controls, patients with epilepsy had decreased resting-state functional connectivity in widespread regions, including perisylvian, posterior temporo-parietal, and orbitofrontal cortices (P < 0.01, t-test). Decreased mean global connectivity was related to longer duration of epilepsy and higher frequency of consciousness-impairing seizures (P < 0.01, linear regression). Furthermore, patients with increased regional connectivity within the resection site (n = 24) were more likely to achieve seizure postoperative seizure freedom (87.5% with Engel I outcome) than those with neutral (n = 15, 64.3% seizure free) or decreased (n = 23, 47.8% seizure free) regional connectivity (P < 0.02, chi-square). Widespread global decreases in functional connectivity are observed in patients with focal epilepsy, and may reflect deleterious long-term effects of recurrent seizures. Furthermore, enhanced regional functional connectivity at the area of resection may help predict seizure outcome and aid surgical planning.

A probabilistic method for determining cortical dynamics during seizures.

This work presents a probabilistic method for inferring the parameter ranges in a biologically relevant mathematical model of the cortex most likely to be producing seizures observed in an electrocorticogram (ECoG) signal from a human subject. Additionally, this method produces a probabilistic pathway of the temporal evolution of physiological state in the cortex over the course of individual seizures, leveraging a model of the cortex that describes cortical physiology. We describe ways in which these methods and results offer insights into seizure etiology and have the potential to suggest new treatment options. To directly account for the stochastic and noisy nature of the mathematical model and the ECoG signal, we use a probabilistic Bayesian framework to map features of ECoG segments onto a distribution of likelihoods over physiologically-relevant parameter states. A Hidden Markov Model (HMM) is then introduced to incorporate the belief that cortical physiology has both temporal continuity and also a degree of reproducibility between individual seizures. By inspecting the ratio of likelihoods between HMMs run under two possible parameter regions, both of which produce seizures in the model, we determine which physiological parameter regions are more likely to be causing the observed seizures. We show that between individual seizures, there is consistency in these likelihood ratios between hypothesized regions, in the temporal pathways calculated, and in the separation of seizure from non-seizure time segment likelihood maps.

Epileptogenic zone localization using magnetoencephalography predicts seizure freedom in epilepsy surgery.

OBJECTIVE: The efficacy of epilepsy surgery depends critically upon successful localization of the epileptogenic zone. Magnetoencephalography (MEG) enables noninvasive detection of interictal spike activity in epilepsy, which can then be localized in three dimensions using magnetic source imaging (MSI) techniques. However, the clinical value of MEG in the presurgical epilepsy evaluation is not fully understood, as studies to date are limited by either a lack of long-term seizure outcomes or small sample size. METHODS: We performed a retrospective cohort study of patients with focal epilepsy who received MEG for interictal spike mapping followed by surgical resection at our institution. RESULTS: We studied 132 surgical patients, with mean postoperative follow-up of 3.6 years (minimum 1 year). Dipole source modeling was successful in 103 patients (78%), whereas no interictal spikes were seen in others. Among patients with successful dipole modeling, MEG findings were concordant with and specific to the following: (1) the region of resection in 66% of patients, (2) invasive electrocorticography (ECoG) findings in 67% of individuals, and (3) the magnetic resonance imaging (MRI) abnormality in 74% of cases. MEG showed discordant lateralization in ~5% of cases. After surgery, 70% of all patients achieved seizure freedom (Engel class I outcome). Whereas 85% of patients with concordant and specific MEG findings became seizure-free, this outcome was achieved by only 37% of individuals with MEG findings that were nonspecific to or discordant with the region of resection (χ(2) = 26.4, p < 0.001). MEG reliability was comparable in patients with or without localized scalp electroencephalography (EEG), and overall, localizing MEG findings predicted seizure freedom with an odds ratio of 5.11 (95% confidence interval [CI] 2.23-11.8). SIGNIFICANCE: MEG is a valuable tool for noninvasive interictal spike mapping in epilepsy surgery, including patients with nonlocalized findings receiving long-term EEG monitoring, and localization of the epileptogenic zone using MEG is associated with improved seizure outcomes.

A probabilistic framework for a physiological representation of dynamically evolving sleep state.

This work presents a probabilistic method for mapping human sleep electroencephalogram (EEG) signals onto a state space based on a biologically plausible mathematical model of the cortex. From a noninvasive EEG signal, this method produces physiologically meaningful pathways of the cortical state over a night of sleep. We propose ways in which these pathways offer insights into sleep-related conditions, functions, and complex pathologies. To address explicitly the noisiness of the EEG signal and the stochastic nature of the mathematical model, we use a probabilistic Bayesian framework to map each EEG epoch to a distribution of likelihoods over all model sleep states. We show that the mapping produced from human data robustly separates rapid eye movement sleep (REM) from slow wave sleep (SWS). A Hidden Markov Model (HMM) is incorporated to improve the path results using the prior knowledge that cortical physiology has temporal continuity.

Open loop optogenetic control of simulated cortical epileptiform activity.

We present a model for the use of open loop optogenetic control to inhibit epileptiform activity in a meso scale model of the human cortex. The meso scale cortical model first developed by Liley et al. (2001) is extended to two dimensions and the nature of the seizure waves is studied. We adapt to the meso scale a 4 state functional model of Channelrhodopsin-2 (ChR2) ion channels. The effects of pulsed and constant illumination on the conductance of these ion channels is presented. The inhibitory cell population is targeted for the application of open loop control. Seizure waves are successfully suppressed and the inherent properties of the optogenetic channels ensures charge balance in the cortex, protecting it from damage.

Sex differences in seizure types and symptoms.

BACKGROUND: Despite the increasing interest in sex differences in disease manifestations and responses to treatment, very few data are available on sex differences in seizure types and semiology. The Epilepsy Phenome/Genome Project (EPGP) is a large-scale, multi-institutional, collaborative study that aims to create a comprehensive repository of detailed clinical information and DNA samples from a large cohort of people with epilepsy. We used this well-characterized cohort to explore differences in seizure types as well as focal seizure symptoms between males and females. METHODS: We reviewed the EPGP database and identified individuals with generalized epilepsy of unknown etiology (GE) (n = 760; female: 446, male: 314), nonacquired focal epilepsy (NAFE) (n = 476; female: 245, male: 231), or both (n = 64; female: 33, male: 31). Demographic data along with characterization of seizure type and focal seizure semiologies were examined. RESULTS: In GE, males reported atonic seizures more frequently than females (6.5% vs. 1.7%; p < 0.001). No differences were observed in other generalized seizure types. In NAFE, no sex differences were seen for seizure types with or without alteration of consciousness or progression to secondary generalization. Autonomic (16.4% vs. 26.6%; p = 0.005), psychic (26.7% vs. 40.3%; p = 0.001), and visual (10.3% vs. 19.9%; p = 0.002) symptoms were more frequently reported in females than males. Specifically, of psychic symptoms, more females than males endorsed déjà vu (p = 0.001) but not forced thoughts, derealization/depersonalization, jamais vu, or fear. With corrections for multiple comparisons, there were no significant differences in aphasic, motor, somatosensory, gustatory, olfactory, auditory, vertiginous, or ictal headache symptoms between sexes. CONCLUSIONS: Significant differences between the sexes were observed in the reporting of atonic seizures, which were more common in males with GE, and for autonomic, visual, and psychic symptoms associated with NAFE, which were more common in females.

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.

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.

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.