Network Disruption and Cerebrospinal Fluid Amyloid-Beta and Phospho-Tau Levels in Mild Cognitive Impairment

Imbalance in the response of pre- and post-synaptic components to amyloidopathy

Alzheimer’s disease (AD)-associated synaptic dysfunction drives the progression of pathology from its earliest stages. Amyloid β (Aβ) species, both soluble and in plaque deposits, have been causally related to the progressive, structural and functional impairments observed in AD. It is, however, still unclear how Aβ plaques develop over time and how they progressively affect local synapse density and turnover. Here we observed, in a mouse model of AD, that Aβ plaques grow faster in the earlier stages of the disease and if their initial area is >500 µm²; this may be due to deposition occurring in the outer regions of the plaque, the plaque cloud. In addition, synaptic turnover is higher in the presence of amyloid pathology and this is paralleled by a reduction in pre- but not post-synaptic densities. Plaque proximity does not appear to have an impact on synaptic dynamics. These observations indicate an imbalance in the response of the pre- and post-synaptic terminals and that therapeutics, alongside targeting the underlying pathology, need to address changes in synapse dynamics.

Aberrant MEG multi-frequency phase temporal synchronization predicts conversion from mild cognitive impairment-to-Alzheimer's disease

Many neuroimaging studies focus on a frequency-specific or a multi-frequency network analysis showing that functional brain networks are disrupted in patients with Alzheimer's disease (AD). Although those studies enriched our knowledge of the impact of AD in brain's functionality, our goal is to test the effectiveness of combining neuroimaging with network neuroscience to predict with high accuracy subjects with mild cognitive impairment (MCI) that will convert to AD. In this study, eyes-closed resting-state magnetoencephalography (MEG) recordings from 27 stable MCI (sMCI) and 27 progressive MCI (pMCI) from two scan sessions (baseline and follow-up after approximately 3 years) were projected via beamforming onto an atlas-based set of regions of interest (ROIs). Dynamic functional connectivity networks were constructed independently for the five classical frequency bands while a multivariate phase-based coupling metric was adopted. Thus, computing the distance between the fluctuation of functional strength of every pair of ROIs between the two conditions with dynamic time wrapping (DTW), a large set of features was extracted. A machine learning algorithm revealed 30 DTW-based features in the five frequency bands that can distinguish the sMCI from pMCI with absolute accuracy (100%). Further analysis of the selected links revealed that most of the connected ROIs were part of the default mode network (DMN), the cingulo-opercular (CO), the fronto-parietal and the sensorimotor network. Overall, our dynamic network multi-frequency analysis approach provides an effective framework of constructing a sensitive MEG-based connectome biomarker for the prediction of conversion from MCI to Alzheimer's disease.

Magnetoencephalography applied to the study of Alzheimer's disease

Magnetoencephalography (MEG) is a relatively modern neuroimaging technique able to study normal and pathological brain functioning with temporal resolution in the order of milliseconds and adequate spatial resolution. Although its clinical applications are still relatively limited, great advances have been made in recent years in the field of dementia and Alzheimer's disease (AD) in particular. In this chapter, we briefly describe the physiological phenomena underlying MEG brain signals and the different metrics that can be computed from these data in order to study the alterations disrupting brain activity not only in demented patients, but also in the preclinical and prodromal stages of the disease. Changes in non-linear brain dynamics, power spectral properties, functional connectivity and network topological changes observed in AD are narratively summarized in the context of the pathophysiology of the disease. Furthermore, the potential of MEG as a potential biomarker to identify AD pathology before dementia onset is discussed in the light of current knowledge and the relationship between potential MEG biomarkers and current established hallmarks of the disease is also reviewed. To this aim, findings from different approaches such as resting state or during the performance of different cognitive paradigms are discussed.Lastly, there is an increasing interest in current scientific literature in promoting interventions aimed at modifying certain lifestyles, such as nutrition or physical activity among others, thought to reduce or delay AD risk. We discuss the utility of MEG as a potential marker of the success of such interventions from the available literature.

The Importance of the Validation of M/EEG With Current Biomarkers in Alzheimer's Disease

Current biomarkers used in research and in clinical practice in Alzheimer's Disease (AD) are the analysis of cerebral spinal fluid (CSF) to detect levels of Aβ42 and phosphorylated-tau, amyloid and FDG-PET, and MRI volumetry. Some of these procedures are still invasive for patients or expensive. Electroencephalography (EEG) and Magnetoencephalography (MEG) are two non-invasive techniques able to detect the early synaptic dysfunction and track the course of the disease. However, in spite of its added value they are not part of the standard of care in clinical practice in dementia. In this paper we review what these neurophysiological techniques can add to the early diagnosis of AD, whether results in both modalities are related to each other or not, as well as the need of its validation against current biomarkers. We discuss their potential implications for the better understanding of the pathophysiological mechanisms of the disease as well as the need of performing simultaneous M/EEG recordings to better understand discrepancies between these two techniques. Finally, more studies are needed studying M/EEG with amyloid and Tau biomarkers.

Relationships Between Diffusion Tensor Imaging and Cerebrospinal Fluid Metrics in Early Stages of the Alzheimer's Disease Continuum

Recently, the field of Alzheimer's disease (AD) research has adopted a new framework that places the progression of AD along a continuum consisting of a preclinical stage, followed by conversion to mild cognitive impairment, and ultimately dementia. Important neuropathological changes occur in the preclinical phase, necessitating the identification of metrics that can detect such early changes. While cerebrospinal fluid (CSF) measures of amyloid and tau are generally accepted as biomarkers of AD pathology, neuroimaging measures used to index white matter alterations throughout the brain remain less widely endorsed as candidate biomarkers. To explore the relationship between white matter alterations and AD pathology, we review the literature on multimodal studies that assessed both CSF markers and white matter indices, derived from diffusion tensor imaging (DTI) methods, across cohorts primarily in the early phases of AD. Our review indicates that abnormal CSF measures of Aβ42 and tau are associated with widespread alterations in white matter microstructure throughout the brain. Furthermore, white matter variability is related to individual differences in behavior and can aid in tracking longitudinal changes in cognition. Our review advocates for the utilization of DTI metrics in investigations of early AD and suggests that the combined use of DTI and CSF markers may better explain individual differences in cognition and disease progression. However, further research is needed to resolve certain mixed findings.

White Matter Injury in Early Brain Injury after Subarachnoid Hemorrhage

Subarachnoid hemorrhage (SAH) is a major cause of high morbidity, disability, and mortality in the field of neurovascular disease. Most previous SAH studies have focused on improving cerebral blood flow, reducing cerebral vasospasm, reducing neuronal calcium overload, and other treatments. While these studies showed exciting findings in basic science, therapeutic strategies based on the findings have not significantly improved neurological outcomes in patients with SAH. Currently, the only drug proven to effectively reduce the neurological defects of SAH patients is nimodipine. Current advances in imaging technologies in the field of stroke have confirmed that white matter injury (WMI) plays an important role in the prognosis of types of stroke, and suggests that WMI protection is essential for functional recovery and poststroke rehabilitation. However, WMI injury in relation to SAH has remained obscure until recently. An increasing number of studies suggest that the current limitations for SAH treatment are probably linked to overlooked WMI in previous studies that focused only on neurons and gray matter. In this review, we discuss the biology and functions of white matter in the normal brain, and discuss the potential pathophysiology and mechanisms of early brain injury after SAH. Our review demonstrates that WMI encompasses multiple substrates, and, therefore, more than one pharmacological approach is necessary to preserve WMI and prevent neurobehavioral impairment after SAH. Strategies targeting both neuronal injury and WMI may potentially provide a novel future for SAH knowledge and treatment.

Functional signature of conversion of patients with mild cognitive impairment

The entorhinal-hippocampal circuit is a strategic hub for cognition and the first site affected by Alzheimer's disease (AD). We investigated magnetic resonance imaging patterns of brain atrophy and functional connectivity in an Alzheimer's Disease Neuroimaging Initiative data set that included healthy controls, mild cognitive impairment (MCI), and patients with AD. Individuals with MCI were clinically evaluated 24 months after the first magnetic resonance imaging scan, and the cohort subdivided into sets of individuals who either did or did not convert to AD. The MCI group was also divided into patients who did show or not the presence of AD-related alterations in the cerebrospinal fluid. Patients with AD exhibited the collapse of the long-range hippocampal/entorhinal connectivity, pronounced cortical/subcortical atrophy, and a dramatic decline in cognitive performances. Patients with MCI who converted to AD or patients with MCI who showed the presence of AD-related alterations in the cerebrospinal fluid showed memory deficits, entorhinal/hippocampal hypoconnectivity, and concomitant atrophy of the two regions. Patients with MCI who did not convert to AD or patients with MCI who did not show the presence of AD-related alterations in the cerebrospinal fluid had no atrophy but showed hippocampal/entorhinal hyperconnectivity with selected neocortical/subcortical regions involved in memory processing and brain metastability. This hyperconnectivity may represent a compensatory strategy against the progression of cognitive impairment.

Healthy and Pathological Brain Aging: From the Perspective of Oscillations, Functional Connectivity, and Signal Complexity

Healthy aging is associated with impairment in cognitive information processing. Several neuroimaging methods such as functional magnetic resonance imaging, positron emission tomography and near-infrared spectroscopy have been used to explore healthy and pathological aging by relying on hemodynamic or metabolic changes that occur in response to brain activity. Since electroencephalography (EEG) and magnetoencephalography (MEG) are able to measure neural activity directly with a high temporal resolution of milliseconds, these neurophysiological techniques are particularly important to investigate the dynamics of brain activity underlying neurocognitive aging. It is well known that age is a major risk factor for Alzheimer's disease (AD), and that synaptic dysfunction represents an early sign of this disease associated with hallmark neuropathological findings. However, the neurophysiological mechanisms underlying AD are not fully elucidated. This review addresses healthy and pathological brain aging from a neurophysiological perspective, focusing on oscillatory activity changes during the resting state, event-related potentials and stimulus-induced oscillatory responses during cognitive or motor tasks, functional connectivity between brain regions, and changes in signal complexity. We also highlight the accumulating evidence on age-related EEG/MEG changes and biological markers of brain neurodegeneration, including genetic factors, structural abnormalities on magnetic resonance images, and the biochemical changes associated with Aβ deposition and tau pathology.

Cognitive Reserve Relates to Functional Network Efficiency in Alzheimer's Disease

Alzheimer’s disease (AD) is the most common form of dementia, with no means of cure or prevention. The presence of abnormal disease-related proteins in the population is, in turn, much more common than the incidence of dementia. In this context, the cognitive reserve (CR) hypothesis has been proposed to explain the discontinuity between pathophysiological and clinical expression of AD, suggesting that CR mitigates the effects of pathology on clinical expression and cognition. fMRI studies of the human connectome have recently reported that AD patients present diminished functional efficiency in resting-state networks, leading to a loss in information flow and cognitive processing. No study has investigated, however, whether CR modifies the effects of the pathology in functional network efficiency in AD patients. We analyzed the relationship between CR, pathophysiology and network efficiency, and whether CR modifies the relationship between them. Fourteen mild AD, 28 amnestic mild cognitive impairment (aMCI) due to AD, and 28 controls were enrolled. We used education to measure CR, cerebrospinal fluid (CSF) biomarkers to evaluate pathophysiology, and graph metrics to measure network efficiency. We found no relationship between CR and CSF biomarkers; CR was related to higher network efficiency in all groups; and abnormal levels of CSF protein biomarkers were related to more efficient networks in the AD group. Education modified the effects of tau-related pathology in the aMCI and mild AD groups. Although higher CR might not protect individuals from developing AD pathophysiology, AD patients with higher CR are better able to cope with the effects of pathology—presenting more efficient networks despite pathology burden. The present study highlights that interventions focusing on cognitive stimulation might be useful to slow age-related cognitive decline or dementia and lengthen healthy aging.

The Role of Magnetoencephalography in the Early Stages of Alzheimer's Disease

The ever increasing proportion of aged people in modern societies is leading to a substantial increase in the number of people affected by dementia, and Alzheimer’s Disease (AD) in particular, which is the most common cause for dementia. Throughout the course of the last decades several different compounds have been tested to stop or slow disease progression with limited success, which is giving rise to a strong interest toward the early stages of the disease. Alzheimer’s disease has an extended an insidious preclinical stage in which brain pathology accumulates slowly until clinical symptoms are observable in prodromal stages and in dementia. For this reason, the scientific community is focusing into investigating early signs of AD which could lead to the development of validated biomarkers. While some CSF and PET biomarkers have already been introduced in the clinical practice, the use of non-invasive measures of brain function as early biomarkers is still under investigation. However, the electrophysiological mechanisms and the early functional alterations underlying preclinical Alzheimer’s Disease is still scarcely studied. This work aims to briefly review the most relevant findings in the field of electrophysiological brain changes as measured by magnetoencephalography (MEG). MEG has proven its utility in some clinical areas. However, although its clinical relevance in dementia is still limited, a growing number of studies highlighted its sensitivity in these preclinical stages. Studies focusing on different analytical approaches will be reviewed. Furthermore, their potential applications to establish early diagnosis and determine subsequent progression to dementia are discussed.

How to Build a Functional Connectomic Biomarker for Mild Cognitive Impairment From Source Reconstructed MEG Resting-State Activity: The Combination of ROI Representation and Connectivity Estimator Matters

Our work aimed to demonstrate the combination of machine learning and graph theory for the designing of a connectomic biomarker for mild cognitive impairment (MCI) subjects using eyes-closed neuromagnetic recordings. The whole analysis based on source-reconstructed neuromagnetic activity. As ROI representation, we employed the principal component analysis (PCA) and centroid approaches. As representative bi-variate connectivity estimators for the estimation of intra and cross-frequency interactions, we adopted the phase locking value (PLV), the imaginary part (iPLV) and the correlation of the envelope (CorrEnv). Both intra and cross-frequency interactions (CFC) have been estimated with the three connectivity estimators within the seven frequency bands (intra-frequency) and in pairs (CFC), correspondingly. We demonstrated how different versions of functional connectivity graphs single-layer (SL-FCG) and multi-layer (ML-FCG) can give us a different view of the functional interactions across the brain areas. Finally, we applied machine learning techniques with main scope to build a reliable connectomic biomarker by analyzing both SL-FCG and ML-FCG in two different options: as a whole unit using a tensorial extraction algorithm and as single pair-wise coupling estimations. We concluded that edge-weighed feature selection strategy outperformed the tensorial treatment of SL-FCG and ML-FCG. The highest classification performance was obtained with the centroid ROI representation and edge-weighted analysis of the SL-FCG reaching the 98% for the CorrEnv in α1:α2 and 94% for the iPLV in α2. Classification performance based on the multi-layer participation coefficient, a multiplexity index reached 52% for iPLV and 52% for CorrEnv. Selected functional connections that build the multivariate connectomic biomarker in the edge-weighted scenario are located in default-mode, fronto-parietal, and cingulo-opercular network. Our analysis supports the notion of analyzing FCG simultaneously in intra and cross-frequency whole brain interactions with various connectivity estimators in beamformed recordings.

Short timescale abnormalities in the states of spontaneous synchrony in the functional neural networks in Alzheimer's disease

Alzheimer's disease (AD) is a prevalent neurodegenerative condition that can lead to severe cognitive and functional deterioration. Functional magnetic resonance imaging (fMRI) revealed abnormalities in AD in intrinsic synchronization between spatially separate regions in the so-called default mode network (DMN) of the brain. To understand the relationship between this disruption in large-scale synchrony and the cognitive impairment in AD, it is critical to determine whether and how the deficit in the low frequency hemodynamic fluctuations recorded by fMRI translates to much faster timescales of memory and other cognitive processes. The present study employed magnetoencephalography (MEG) and a Hidden Markov Model (HMM) approach to estimate spontaneous synchrony variations in the functional neural networks with high temporal resolution. In a group of cognitively healthy (CH) older adults, we found transient (mean duration of 150-250 ms) network activity states, which were visited in a rapid succession, and were characterized by spatially coordinated changes in the amplitude of source-localized electrophysiological oscillations. The inferred states were similar to those previously observed in younger participants using MEG, and the estimated cortical source distributions of the state-specific activity resembled the classic functional neural networks, such as the DMN. In patients with AD, inferred network states were different from those of the CH group in short-scale timing and oscillatory features. The state of increased oscillatory amplitudes in the regions overlapping the DMN was visited less often in AD and for shorter periods of time, suggesting that spontaneous synchronization in this network was less likely and less stable in the patients. During the visits to this state, in some DMN nodes, the amplitude change in the higher-frequency (8-30 Hz) oscillations was less robust in the AD than CH group. These findings highlight relevance of studying short-scale temporal evolution of spontaneous activity in functional neural networks to understanding the AD pathophysiology. Capacity of flexible intrinsic synchronization in the DMN may be crucial for memory and other higher cognitive functions. Our analysis yielded metrics that quantify distinct features of the neural synchrony disorder in AD and may offer sensitive indicators of the neural network health for future investigations.

Subjective Cognitive Decline Is Associated With Altered Default Mode Network Connectivity in Individuals With a Family History of Alzheimer's Disease

BACKGROUND

Both subjective cognitive decline (SCD) and a family history of Alzheimer's disease (AD) portend risk of brain abnormalities and progression to dementia. Posterior default mode network (pDMN) connectivity is altered early in the course of AD. It is unclear whether SCD predicts similar outcomes in cognitively normal individuals with a family history of AD.

METHODS

We studied 124 asymptomatic individuals with a family history of AD (age 64 ± 5 years). Participants were categorized as having SCD if they reported that their memory was becoming worse (SCD⁺). We used extensive neuropsychological assessment to investigate five different cognitive domain performances at baseline (n = 124) and 1 year later (n = 59). We assessed interconnectivity among three a priori defined ROIs: pDMN, anterior ventral DMN, medial temporal memory system (MTMS), and the connectivity of each with the rest of brain.

RESULTS

Sixty-eight (55%) participants reported SCD. Baseline cognitive performance was comparable between groups (all false discovery rate-adjusted p values > .05). At follow-up, immediate and delayed memory improved across groups, but the improvement in immediate memory was reduced in SCD⁺ compared with SCD^- (all false discovery rate-adjusted p values < .05). When compared with SCD^-, SCD⁺ subjects showed increased pDMN-MTMS connectivity (false discovery rate-adjusted p < .05). Higher connectivity between the MTMS and the rest of the brain was associated with better baseline immediate memory, attention, and global cognition, whereas higher MTMS and pDMN-MTMS connectivity were associated with lower immediate memory over time (all false discovery rate-adjusted p values < .05).

CONCLUSIONS

SCD in cognitively normal individuals is associated with diminished immediate memory practice effects and a brain connectivity pattern that mirrors early AD-related connectivity failure.

Immune and Imaging Correlates of Mild Cognitive Impairment Conversion to Alzheimer's Disease

Amnestic mild cognitive impairment (aMCI) conversion to Alzheimer’s disease (AD) is seen in a sizable portion of aMCI patients; correlates predicting such conversion are poorly defined but neuroinflammation and the reactivation of chronic viral infections are suspected to play a role in this phenomenon. We analyzed these aspects in two homogeneous groups of aMCI who did or did not convert to AD over a 24-months period. Results showed that at baseline in those aMCI individuals who did not convert to AD: 1) Aβ_1-42 stimulated production of the pro-inflammatory cytokines IL6 and IL1β by CD14⁺ cells was significantly reduced (p = 0.01), 2) CD14⁺/IL-33⁺ cells were increased (p = 0.0004); 3) MFI of TLR8 and TLR9 was significantly increased, and 4) better preserved hippocampus volumes were observed and correlated with IL33⁺/CD14⁺ cells. Notably, Aβ_1-42 stimulated production of the antiviral cytokine IFN-λ was increased as well in non-AD converters, although with a borderline statistical significance (p = 0.05). Data herein indicating that proinflammatory cytokines are reduced, whereas IFN-λ production and TLR8 and 9 MFI are augmented in those aMCI in whom AD conversion is not observed suggest that the ability to mount stronger antiviral response within an antiiflammatory milieu associates with lack of AD conversion.

Emergence of early alterations in network oscillations and functional connectivity in a tau seeding mouse model of Alzheimer's disease pathology

Synaptic dysfunction and disconnectivity are core deficits in Alzheimer’s disease (AD), preceding clear changes in histopathology and cognitive functioning. Here, the early and late effects of tau pathology induction on functional network connectivity were investigated in P301L mice. Multichannel EEG oscillations were used to compute (1) coherent activity between the prefrontal cortex (PFC) and hippocampus (HPC) CA1-CA3 networks; (2) phase-amplitude cross frequency coupling (PAC) between theta and gamma oscillations, which is instrumental in adequate cognitive functioning; (3) information processing as assessed by auditory evoked potentials and oscillations in the passive oddball mismatch negativity-like (MMN) paradigm. At the end, the density of tau aggregation and GABA parvalbumin (PV+) interneurons were quantified by immunohistochemistry. Early weakening of EEG theta oscillations and coherent activity were revealed between the PFC and HPC CA1 and drastic impairments in theta–gamma oscillations PAC from week 2 onwards, while PV+ interneurons count was not altered. Moreover, the tau pathology disrupted the MMN complex amplitude and evoked gamma oscillations to standard and deviant stimuli suggesting altered memory formation and recall. The induction of intracellular tau aggregation by tau seed injection results in early altered connectivity and strong theta–gamma oscillations uncoupling, which may be exploited as an early electrophysiological signature of dysfunctional neuronal networks.

Early functional network alterations in asymptomatic elders at risk for Alzheimer's disease

Amyloid-β (Aβ) deposition is known to starts decades before the onset of clinical symptoms of Alzheimer's disease (AD), however, the detailed pathophysiological processes underlying this preclinical period are not well understood. This study aimed to investigate functional network alterations in cognitively intact elderly individuals at risk for AD, and assessed the association between these network alterations and changes in Aβ deposition, glucose metabolism, and brain structure. Forty-five cognitively normal elderly subjects, who were classified into Aβ-positive (CN+) and Aβ-negative (CN-) groups using ¹¹C-Pittsburgh compound B PET, underwent resting state magnetoencephalography measurements, ¹⁸F-fluorodeoxyglucose PET (FDG-PET) and structural MRI. Results demonstrated that in the CN+ group, functional connectivity (FC) within the precuneus was significantly decreased, whereas it was significantly enhanced between the precuneus and the bilateral inferior parietal lobules in the low-frequency bands (theta and delta). These changes were suggested to be associated with local cerebral Aβ deposition. Most of Aβ+ individuals in this study did not show any metabolic or anatomical changes, and there were no significant correlations between FC values and FDG-PET or MRI volumetry data. These results demonstrate that functional network alterations, which occur in association with Aβ deposition, are detectable using magnetoencephalography before metabolic and anatomical changes are seen.

MEG biomarker of Alzheimer's disease: Absence of a prefrontal generator during auditory sensory gating

Magnetoencephalography (MEG), a direct measure of neuronal activity, is an underexplored tool in the search for biomarkers of Alzheimer's disease (AD). In this study, we used MEG source estimates of auditory gating generators, nonlinear correlations with neuropsychological results, and multivariate analyses to examine the sensitivity and specificity of gating topology modulation to detect AD. Our results demonstrated the use of MEG localization of a medial prefrontal (mPFC) gating generator as a discrete (binary) detector of AD at the individual level and resulted in recategorizing the participant categories in: (1) controls with mPFC generator localized in response to both the standard and deviant tones; (2) a possible preclinical stage of AD participants (a lower functioning group of controls) in which mPFC activation was localized to the deviant tone only; and (3) symptomatic AD in which mPFC activation was not localized to either the deviant or standard tones. This approach showed a large effect size (0.9) and high accuracy, sensitivity, and specificity (100%) in identifying symptomatic AD patients within a limited research sample. The present results demonstrate high potential of mPFC activation as a noninvasive biomarker of AD pathology during putative preclinical and clinical stages. Hum Brain Mapp 38:5180-5194, 2017. © 2017 Wiley Periodicals, Inc.

MEG Beamformer-Based Reconstructions of Functional Networks in Mild Cognitive Impairment

Subjects with mild cognitive impairment (MCI) have an increased risk of developing Alzheimer’s disease (AD), and their functional brain networks are presumably already altered. To test this hypothesis, we compared magnetoencephalography (MEG) eyes-closed resting-state recordings from 29 MCI subjects and 29 healthy elderly subjects in the present exploratory study. Functional connectivity in different frequency bands was assessed with the phase lag index (PLI) in source space. Normalized weighted clustering coefficient (normalized Cw) and path length (normalized Lw), as well as network measures derived from the minimum spanning tree [MST; i.e., betweenness centrality (BC) and node degree], were calculated. First, we found altered PLI values in the lower and upper alpha bands in MCI patients compared to controls. Thereafter, we explored network differences in these frequency bands. Normalized Cw and Lw did not differ between the groups, whereas BC and node degree of the MST differed, although these differences did not survive correction for multiple testing using the False Discovery Rate (FDR). As an exploratory study, we may conclude that: (1) the increases and decreases observed in PLI values in lower and upper alpha bands in MCI patients may be interpreted as a dual pattern of disconnection and aberrant functioning; (2) network measures are in line with connectivity findings, indicating a lower efficiency of the brain networks in MCI patients; (3) the MST centrality measures are more sensitive to detect subtle differences in the functional brain networks in MCI than traditional graph theoretical metrics.

Tau and amyloid β proteins distinctively associate to functional network changes in the aging brain

INTRODUCTION

Misfolded tau and amyloid β (Aβ) proteins progressively accumulate in the human brain, causing altered neuronal function and neurodegeneration. This study sought to investigate whether the wide spectrum of functional reorganization in aging brains of cognitively normal individuals relates to specific pathological patterns of tau and Aβ deposits.

METHODS

We used functional connectivity neuroimaging and in vivo tau and Aβ positron emission tomography scans to study cortical spatial relationships between imaging modalities.

RESULTS

We found that a negative association between tau and functional connectivity combined with a positive association between Aβ and functional connectivity is the most frequent cortical pattern among elderly subjects. Moreover, we found specific brain areas that interrelate hypoconnectivity and hyperconnectivity regions.

DISCUSSION

Our findings have critical implications to understanding how the two main elements of Alzheimer's disease-related pathology affect the aging brain and how they cause alterations in large-scale neuronal circuits.

Searching for Primary Predictors of Conversion from Mild Cognitive Impairment to Alzheimer's Disease: A Multivariate Follow-Up Study

Recent proposals of diagnostic criteria within the healthy aging-Alzheimer's disease (AD) continuum stressed the role of biomarker information. More importantly, such information might be critical to predict those mild cognitive impairment (MCI) patients at a higher risk of conversion to AD. Usually, follow-up studies utilize a reduced number of potential markers although the conversion phenomenon may be deemed as multifactorial in essence. In addition, not only biological but also cognitive markers may play an important role. Considering this background, we investigated the role of cognitive reserve, cognitive performance in neuropsychological testing, hippocampal volumes, APOE genotype, and magnetoencephalography power sources to predict the conversion to AD in a sample of 33 MCI patients. MCIs were followed up during a 2-year period and divided into two subgroups according to their outcome: The "stable" MCI group (sMCI, 21 subjects) and the "progressive" MCI group (pMCI, 12 subjects). Baseline multifactorial information was submitted to a hierarchical logistic regression analysis to build a predictive model of conversion to AD. Results indicated that the combination of left hippocampal volume, occipital cortex theta power, and clock drawing copy subtest scores predicted conversion to AD with a 100% of sensitivity and 94.7% of specificity. According to these results it might be suggested that anatomical, cognitive, and neurophysiological markers may be considered as "first order" predictors of progression to AD, while APOE or cognitive reserve proxies might play a more secondary role.

Inter-hemispheric functional dysconnectivity mediates the association of corpus callosum degeneration with memory impairment in AD and amnestic MCI

Evidences suggested that both corpus callosum (CC) degeneration and alternations of homotopic inter-hemispheric functional connectivity (FC) are present in Alzheimer's disease (AD). However, the associations between region-specific CC degeneration and homotopic inter-hemispheric FC and their relationships with memory deficits in AD remain uncharacterized. We hypothesized that selective CC degeneration is associated with memory impairment in AD and amnestic mild cognitive impairment (aMCI), which is mediated by homotopic inter-hemispheric functional dysconnectivity. Using structural magnetic resonance imaging (MRI) and task-free functional MRI, we assessed the CC volume and inter-hemispheric FC in 66 healthy controls, 41 aMCI and 41 AD. As expected, AD had CC degeneration and attenuated inter-hemispheric homotopic FC. Nevertheless, aMCI had relatively less severe CC degeneration (mainly in mid-anterior, central, and mid-posterior) and no reduction in inter-hemispheric homotopic FC. The degeneration of each CC sub-region was associated with specific inter-hemispheric homotopic functional disconnections in AD and aMCI. More importantly, impairment of inter-hemispheric homotopic FC partially mediated the association between CC (particularly the central and posterior parts) degeneration and memory deficit. Notably, these results remained after controlling for hippocampal volume. Our findings shed light on how CC degeneration and the related inter-hemispheric FC impact memory impairment in early stage of AD.

Atrophy of amygdala and abnormal memory-related alpha oscillations over posterior cingulate predict conversion to Alzheimer's disease

Synaptic dysfunction, a key pathophysiological hallmark of Alzheimer’s disease (AD), may account for abnormal memory-related EEG patterns in prodromal AD. Here, we investigate to what extent oscillatory EEG changes during memory encoding and/or retrieval enhance the accuracy of medial temporal lobe (MTL) atrophy in predicting conversion from amnestic mild cognitive impairment (aMCI) to AD. As expected, aMCI individuals that, within a 2-year follow-up period, developed dementia (N = 16) compared to healthy older (HO) (N = 26) and stable aMCI (N = 18) showed poorer associative memory, greater MTL atrophy, and lower capacity to recruit alpha oscillatory cortical networks. Interestingly, encoding-induced abnormal alpha desynchronized activity over the posterior cingulate cortex (PCC) at baseline showed significantly higher accuracy in predicting AD than the magnitude of amygdala atrophy. Nevertheless, the best accuracy was obtained when the two markers were fitted into the model (sensitivity = 78%, specificity = 82%). These results support the idea that synaptic integrity/function in the PCC is affected during prodromal AD and has the potential of improving early detection when combined with MRI biomarkers.

Unbiased Stereological Analysis of Reactive Astrogliosis to Estimate Age-Associated Cerebral White Matter Injury

Cerebral white matter injury (WMI) contributes to cognitive dysfunction associated with pathological aging. Because reactive astrocyte-related factors contribute to remyelination failure after WMI, we sought accurate, cost-effective, and reproducible histopathological approaches for quantification of morphometric features of reactive astrogliosis in aged human white matter in patients with vascular brain injury (VBI). We compared 7 distinct approaches to quantify the features of glial fibrillary acidic protein (GFAP)-labeled astrocytes in the prefrontal white matter of brains from patients with VBI (n = 17, mean age 88.8 years) and controls that did not exhibit VBI (n = 11, mean age 86.6 years). Only modern stereological techniques (ie, optical fractionator and spaceballs) and virtual process thickness measurements demonstrated significant changes in astrocyte number, process length, or proximal process thickness in cases with VBI relative to controls. The widely employed methods of neuropathological scoring, antibody capture assay (histelide), area fraction fractionator, and Cavalieri point counting failed to detect significant differences in GFAP expression between the groups. Unbiased stereological approaches and virtual thickness measurements provided the only sensitive and accurate means to quantify astrocyte reactivity as a surrogate marker of WMI in human brains with VBI.

Self, cortical midline structures and the resting state: Implications for Alzheimer's disease

Different aspects of the self have been reported to be affected in many neurological or psychiatric diseases such as Alzheimer's disease (AD), including mainly higher-level cognitive self-unawareness. This higher sense of self-awareness is most likely related to and dependent on episodic memory, due to the proper integration of ourselves in time, with a permanent conservation of ourselves (i.e., sense of continuity across time). Reviewing studies in this field, our objective is thus to raise possible explanations, especially with the help of neuroimaging studies, for where such self-awareness deficits originate in AD patients. We describe not only episodic (and autobiographical memory) impairment in patients, but also the important role of cortical midline structures, the Default Mode Network, and the resting state (intrinsic brain activity) for the processing of self-related information.

Comparison between Early-Onset and Late-Onset Alzheimer's Disease Patients with Amnestic Presentation: CSF and (18)F-FDG PET Study

Background/Aims

To investigate the differences in brain glucose consumption between patients with early onset of Alzheimer's disease (EOAD, aged ≤65 years) and patients with late onset of Alzheimer's disease (LOAD, aged >65 years).

Methods

Differences in brain glucose consumption between the groups have been evaluated by means of Statistical Parametric Mapping version 8, with the use of age, sex, Mini-Mental State Examination and cerebrospinal fluid values of AΒ_1-42, phosphorylated Tau and total Tau as covariates in the comparison between EOAD and LOAD.

Results

As compared to LOAD, EOAD patients showed a significant decrease in glucose consumption in a wide portion of the left parietal lobe (BA7, BA31 and BA40). No significant differences were obtained when subtracting the EOAD from the LOAD group.

Conclusions

The results of our study show that patients with EOAD show a different metabolic pattern as compared to those with LOAD that mainly involves the left parietal lobe.

Quantitative and semi-quantitative measurements of axonal degeneration in tissue and primary neuron cultures

BACKGROUND

Axon viability is critical for maintaining neural connectivity, which is central to neural functionality. Many neurodegenerative diseases (e.g., Parkinson's disease (PD) and Alzheimer's disease) appear to involve extensive axonal degeneration that often precedes somatic loss in affected neural populations. Axonal degeneration involves a number of intracellular pathways and characteristic changes in axon morphology (i.e., swelling, fragmentation, and loss).

NEW METHOD

We describe a relatively simple set of methods to quantify the axonal degeneration using the 6-hydroxydopamine neurotoxin model of PD in rats and a colchicine-induced model in primary rat neurons. Specifically, approaches are described that use the spaceballs stereological probe for tissue sections and petrimetrics stereological probe for cultured neurons, and image analysis techniques in both tissue sections and cultured neurons.

RESULTS

These methods provide a mechanism for obtaining quantitative and semi-quantitative data to track the extent of axonal degeneration and may prove useful as outcome measures in studies aimed at preventing or slowing axonal degeneration in disease models.

COMPARISON WITH EXISTING METHODS

Existing methods of quantification of axonal degeneration use densitometry and manual counts of axonal projections, but they do not utilize the random, unbiased systematic sampling approaches that are characteristic of stereological methods. The ImageJ thresholding analyses described here provide a descriptive method for quantifying the state of axonal degeneration.

CONCLUSIONS

These methods provide an efficient and effective means to quantify the extent and state of axonal degeneration in animal tissue and cultured neurons and can be used in other models for the same purposes.