Functional magnetic resonance imaging as a dynamic candidate biomarker for Alzheimer's disease

Functional connectivity changes in mild cognitive impairment: A meta-analysis of M/EEG studies

OBJECTIVE

Early synchrony alterations have been observed through electrophysiological techniques in Mild Cognitive Impairment (MCI), which is considered the intermediate phase between healthy aging (HC) and Alzheimer's disease (AD). However, the documented direction (hyper/hypo-synchronization), regions and frequency bands affected are inconsistent. This meta-analysis intended to elucidate existing evidence linked to potential neurophysiological biomarkers of AD.

METHODS

We conducted a random-effects meta-analysis that entailed the unbiased inclusion of Non-statistically Significant Unreported Effect Sizes ("MetaNSUE") of electroencephalogram (EEG) and magnetoencephalogram (MEG) studies investigating functional connectivity changes at rest along the healthy-pathological aging continuum, searched through PubMed, Scopus, Web of Science and PsycINFO databases until June 2023.

RESULTS

Of the 3852 articles extracted, we analyzed 12 papers, and we found an alpha synchrony decrease in MCI compared to HC, specifically between temporal-parietal (d = -0.26) and frontal-parietal areas (d = -0.25).

CONCLUSIONS

Alterations of alpha synchrony are present even at MCI stage.

SIGNIFICANCE

Synchrony measures may be promising for the detection of the first hallmarks of connectivity alterations, even at the prodromal stages of the AD, before clinical symptoms occur.

Resting-state functional connectivity is modulated by cognitive reserve in early Parkinson's disease

Background

Fronto-striatal disconnection is thought to be at the basis of dysexecutive symptoms in patients with Parkinson's disease (PD). Multiple reserve-related processes may offer resilience against functional decline. Among these, cognitive reserve (CR) refers to the adaptability of cognitive processes.

Objective

To test the hypothesis that functional connectivity of pathways associated with executive dysfunction in PD is modulated by CR.

Methods

Twenty-six PD patients and 24 controls underwent resting-state functional magnetic resonance imaging. Functional connectivity was explored with independent component analysis and seed-based approaches. The following networks were selected from the outcome of the independent component analysis: default-mode (DMN), left and right fronto-parietal (l/rFPN), salience (SalN), sensorimotor (SMN), and occipital visual (OVN). Seed regions were selected in the substantia nigra and in the dorsolateral and ventromedial prefrontal cortex for the assessment of seed-based functional connectivity maps. Educational and occupational attainments were used as CR proxies.

Results

Compared with their counterparts with high CR, PD individuals with low CR had reduced posterior DMN functional connectivity in the anterior cingulate and basal ganglia, and bilaterally reduced connectivity in fronto-parietal regions within the networks defined by the dorsolateral and ventrolateral prefrontal seeds. Hyper-connectivity was detected within medial prefrontal regions when comparing low-CR PD with low-CR controls.

Conclusion

CR may exert a modulatory effect on functional connectivity in basal ganglia and executive-attentional fronto-parietal networks. In PD patients with low CR, attentional control networks seem to be downregulated, whereas higher recruitment of medial frontal regions suggests compensation via an upregulation mechanism. This upregulation might contribute to maintaining efficient cognitive functioning when posterior cortical function is progressively reduced.

Effects of repetitive transcranial magnetic stimulation and their underlying neural mechanisms evaluated with magnetic resonance imaging-based brain connectivity network analyses

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive brain modulation and rehabilitation technique used in patients with neuropsychiatric diseases. rTMS can structurally remodel or functionally induce activities of specific cortical regions and has developed to an important therapeutic method in such patients. Magnetic resonance imaging (MRI) provides brain data that can be used as an explanation tool for the neural mechanisms underlying rTMS effects; brain alterations related to different functions or structures may be reflected in changes in the interaction and influence of brain connections within intrinsic specific networks. In this review, we discuss the technical details of rTMS and the biological interpretation of brain networks identified with MRI analyses, comprehensively summarize the neurobiological effects in rTMS-modulated individuals, and elaborate on changes in the brain network in patients with various neuropsychiatric diseases receiving rehabilitation treatment with rTMS. We conclude that brain connectivity network analysis based on MRI can reflect alterations in functional and structural connectivity networks comprising adjacent and separated brain regions related to stimulation sites, thus reflecting the occurrence of intrinsic functional integration and neuroplasticity. Therefore, MRI is a valuable tool for understanding the neural mechanisms of rTMS and practically tailoring treatment plans for patients with neuropsychiatric diseases.

EEG and fMRI coupling and decoupling based on joint independent component analysis (jICA)

BACKGROUND

Meaningful integration of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) requires knowing whether these measurements reflect the activity of the same neural sources, i.e., estimating the degree of coupling and decoupling between the neuroimaging modalities.

NEW METHOD

This paper proposes a method to quantify the coupling and decoupling of fMRI and EEG signals based on the mixing matrix produced by joint independent component analysis (jICA). The method is termed fMRI/EEG-jICA.

RESULTS

fMRI and EEG acquired during a syllable detection task with variable syllable presentation rates (0.25-3 Hz) were separated with jICA into two spatiotemporally distinct components, a primary component that increased nonlinearly in amplitude with syllable presentation rate, putatively reflecting an obligatory auditory response, and a secondary component that declined nonlinearly with syllable presentation rate, putatively reflecting an auditory attention orienting response. The two EEG subcomponents were of similar amplitude, but the secondary fMRI subcomponent was ten folds smaller than the primary one.

COMPARISON TO EXISTING METHOD

FMRI multiple regression analysis yielded a map more consistent with the primary than secondary fMRI subcomponent of jICA, as determined by a greater area under the curve (0.5 versus 0.38) in a sensitivity and specificity analysis of spatial overlap.

CONCLUSION

fMRI/EEG-jICA revealed spatiotemporally distinct brain networks with greater sensitivity than fMRI multiple regression analysis, demonstrating how this method can be used for leveraging EEG signals to inform the detection and functional characterization of fMRI signals. fMRI/EEG-jICA may be useful for studying neurovascular coupling at a macro-level, e.g., in neurovascular disorders.

Recurrent and concurrent patterns of regional BOLD dynamics and functional connectivity dynamics in cognitive decline

Background

The brain’s dynamic spontaneous neural activity and dynamic functional connectivity (dFC) are both important in supporting cognition, but how these two types of brain dynamics evolve and co-evolve in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remain unclear. The aim of the present study was to investigate recurrent and concurrent patterns of two types of dynamic brain states correlated with cognitive decline.

Methods

The present study analyzed resting-state functional magnetic resonance imaging data from 62 SCD patients, 75 MCI patients, and 70 healthy controls (HCs). We used the sliding-window and clustering method to identify two types of recurrent brain states from both dFC and dynamic regional spontaneous activity, as measured by dynamic fractional amplitude of low-frequency fluctuations (dfALFF). Then, the occurrence frequency of a dFC or dfALFF state and the co-occurrence frequency of a pair of dFC and dfALFF states among all time points are extracted for each participant to describe their dynamics brain patterns.

Results

We identified a few recurrent states of dfALFF and dFC and further ascertained the co-occurrent patterns of these two types of dynamic brain states (i.e., dfALFF and dFC states). Importantly, the occurrence frequency of a default-mode network (DMN)-dominated dFC state was significantly different between HCs and SCD patients, and the co-occurrence frequencies of a DMN-dominated dFC state and a DMN-dominated dfALFF state were also significantly different between SCD and MCI patients. These two dynamic features were both significantly positively correlated with Mini-Mental State Examination scores.

Conclusion

Our findings revealed novel fMRI-based neural signatures of cognitive decline from recurrent and concurrent patterns of dfALFF and dFC, providing strong evidence supporting SCD as the transition phase between normal aging and MCI. This finding holds potential to differentiate SCD patients from HCs via both dFC and dfALFF as objective neuroimaging biomarkers, which may aid in the early diagnosis and intervention of Alzheimer’s disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-020-00764-6.

Connectome-based models can predict processing speed in older adults

Decrement in processing speed (PS) is a primary cognitive morbidity in clinical populations and could significantly influence other cognitive functions, such as attention and memory. Verifying the usefulness of connectome-based models for predicting neurocognitive abilities has significant translational implications on clinical and aging research. In this study, we verified that resting-state functional connectivity could be used to predict PS in 99 older adults by using connectome-based predictive modeling (CPM). We identified two distinct connectome patterns across the whole brain: the fast-PS and slow-PS networks. Relative to the slow-PS network, the fast-PS network showed more within-network connectivity in the motor and visual networks and less between-network connectivity in the motor-visual, motor-subcortical/cerebellum and motor-frontoparietal networks. We further verified that the connectivity patterns for prediction of PS were also useful for predicting attention and memory in the same sample. To test the generalizability and specificity of the connectome-based predictive models, we applied these two connectome models to an independent sample of three age groups (101 younger adults, 103 middle-aged adults and 91 older adults) and confirmed these models could specifically be generalized to predict PS of the older adults, but not the younger and middle-aged adults. Taking all the findings together, the identified connectome-based predictive models are strong for predicting PS in older adults. The application of CPM to predict neurocognitive abilities can complement conventional neurocognitive assessments, bring significant clinical benefits to patient management and aid the clinical diagnoses, prognoses and management of people undergoing the aging process.

Neuronal correlates of the visual-spatial processing measured with functional near-infrared spectroscopy in healthy elderly individuals

Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) are a globally rising issue. It is necessary to detect such diseases early to find strategies for prevention. Typically, patients with MCI or AD show deviant neuronal patterns, which could be detected early through brain imaging techniques enabling assumptions about pre-existing diseases. Functional Near-Infrared Spectroscopy (fNIRS) is an appropriate imaging method because of its easy and economical nature with hardly any drawbacks. An early measurable risk factor indicating neurodegenerative processes could be a deficit in visual-spatial processing, which is localized in the parietal cortex. In this study, we aimed to measure the hemodynamic response of the visual-spatial processing in the healthy elderly participants of our long-term Vogel Study with fNIRS during the clock-hand-angle-discrimination task (ADT) to deepen our understanding of healthy brain mechanisms. Our results revealed for our healthy sample a significantly increased neuronal brain activity with increasing task difficulties, namely from the long to the middle to the short clock hand during ADT and significantly higher activation in the right hemisphere compared to the left hemisphere as well as in the superior parietal cortex compared to the inferior parietal cortex. Additionally, our behavioral data demonstrated longer reaction times and more errors with an increasing task requirement. We, therefore, assume that visual-spatial processing can successfully be operationalized with fNIRS for healthy elderly people based on ADT. Further fNIRS analyses are planned to investigate pathological neuronal correlates of visual-spatial function in MCI or AD study participants.

Functional Connectivity of Default Mode Network Subsystems in the Presymptomatic Stage of Autosomal Dominant Alzheimer's Disease

BACKGROUND

The default mode network (DMN) could be divided into subsystems, the functional connectivity of which are different across the Alzheimer's disease (AD) spectrum. However, the functional connectivity patterns within the subsystems are unknown in presymptomatic autosomal dominant AD (ADAD).

OBJECTIVE

To investigate functional connectivity patterns within the subsystems of the DMN in presymptomatic subjects carrying PSEN1, PSEN2, or APP gene mutations.

METHODS

Twenty-six presymptomatic mutation carriers (PMC) and twenty-nine cognitively normal non-carriers as normal controls (NC) from the same families underwent resting state functional MRI and structural MRI. Seed-based analyses were done to obtain functional connectivity of posterior and anterior DMN. For the regions that showed significant connectivity difference between PMC and NC, volumes were extracted and compared between the two groups. Connectivity measures were then correlated with cognitive tests scores.

RESULTS

The posterior DMN showed connectivity decrease in the PMC group as compared with the NC group, which was primarily the connectivity of left precuneus with right precuneus and superior frontal gyrus; the anterior DMN showed significant connectivity decrease in the PMC group, which was the connectivity of medial frontal gyrus with middle frontal gyrus. In the brain regions showing connectivity changes in the PMC group, there was no group difference in volume. A positive correlation was observed between the precuneus connectivity value and Mini-Mental State Examination total score.

CONCLUSION

Functional connectivity within both posterior and anterior DMN were disrupted in the presymptomatic stage of ADAD. Connectivity disruption within the posterior DMN may be useful for early identification of general cognitive decline and a potential imaging biomarker for early diagnosis.

A study of within-subject reliability of the brain's default-mode network

Objective

Resting-state functional magnetic resonance imaging (fMRI) is promising for Alzheimer’s disease (AD). This study aimed to examine short-term reliability of the default-mode network (DMN), one of the main haemodynamic patterns of the brain.

Materials and methods

Using a 1.5 T Philips Achieva scanner, two consecutive resting-state fMRI runs were acquired on 69 healthy adults, 62 patients with mild cognitive impairment (MCI) due to AD, and 28 patients with AD dementia. The anterior and posterior DMN and, as control, the visual-processing network (VPN) were computed using two different methodologies: connectivity of predetermined seeds (theory-driven) and dual regression (data-driven). Divergence and convergence in network strength and topography were calculated with paired t tests, global correlation coefficients, voxel-based correlation maps, and indices of reliability.

Results

No topographical differences were found in any of the networks. High correlations and reliability were found in the posterior DMN of healthy adults and MCI patients. Lower reliability was found in the anterior DMN and in the VPN, and in the posterior DMN of dementia patients.

Discussion

Strength and topography of the posterior DMN appear relatively stable and reliable over a short-term period of acquisition but with some degree of variability across clinical samples.

Positive Connectivity Predicts the Dynamic Intrinsic Topology of the Human Brain Network

Functional connectivity MRI (fcMRI) has become instrumental in facilitating research of human brain network organization in terms of coincident interactions between positive and negative synchronizations of large-scale neuronal systems. Although there is a common agreement concerning the interpretation of positive couplings between brain areas, a major debate has been made in disentangling the nature of negative connectivity patterns in terms of its emergence in several methodological approaches and its significance/meaning in specific neuropsychiatric diseases. It is still not clear what information the functional negative correlations or connectivity provides or how they relate to the positive connectivity. Through implementing stepwise functional connectivity (SFC) analysis and studying the causality of functional topological patterns, this study aims to shed light on the relationship between positive and negative connectivity in the human brain functional connectome. We found that the strength of negative correlations between voxel-pairs relates to their positive connectivity path-length. More importantly, our study describes how the spatio-temporal patterns of positive connectivity explain the evolving changes of negative connectivity over time, but not the other way around. This finding suggests that positive and negative connectivity do not display equivalent forces but shows that the positive connectivity has a dominant role in the overall human brain functional connectome. This phenomenon provides novel insights about the nature of positive and negative correlations in fcMRI and will potentially help new developments for neuroimaging biomarkers.

Machine-learning Support to Individual Diagnosis of Mild Cognitive Impairment Using Multimodal MRI and Cognitive Assessments

BACKGROUND

Understanding whether the cognitive profile of a patient indicates mild cognitive impairment (MCI) or performance levels within normality is often a clinical challenge. The use of resting-state functional magnetic resonance imaging (RS-fMRI) and machine learning may represent valid aids in clinical settings for the identification of MCI patients.

METHODS

Machine-learning models were computed to test the classificatory accuracy of cognitive, volumetric [structural magnetic resonance imaging (sMRI)] and blood oxygen level dependent-connectivity (extracted from RS-fMRI) features, in single-modality and mixed classifiers.

RESULTS

The best and most significant classifier was the RS-fMRI+Cognitive mixed classifier (94% accuracy), whereas the worst performing was the sMRI classifier (∼80%). The mixed global (sMRI+RS-fMRI+Cognitive) had a slightly lower accuracy (∼90%), although not statistically different from the mixed RS-fMRI+Cognitive classifier. The most important cognitive features were indices of declarative memory and semantic processing. The crucial volumetric feature was the hippocampus. The RS-fMRI features selected by the algorithms were heavily based on the connectivity of mediotemporal, left temporal, and other neocortical regions.

CONCLUSION

Feature selection was profoundly driven by statistical independence. Some features showed no between-group differences, or showed a trend in either direction. This indicates that clinically relevant brain alterations typical of MCI might be subtle and not inferable from group analysis.

Effects of resveratrol on memory performance, hippocampus connectivity and microstructure in older adults - A randomized controlled trial

INTRODUCTION

The polyphenol resveratrol has been suggested to exert beneficial effects on memory and the aging hippocampus due to calorie-restriction mimicking effects. However, the evidence based on human interventional studies is scarce. We therefore aimed to determine the effects of resveratrol on memory performance, and to identify potential underlying mechanisms using a broad array of blood-based biomarkers as well as hippocampus connectivity and microstructure assessed with ultra-high field magnetic resonance imaging (UHF-MRI).

METHODS

In this double-blind, randomized controlled trial, 60 elderly participants (60-79 years) with a wide body-mass index (BMI) range of 21-37 kg/m² were randomized to receive either resveratrol (200 mg/day) or placebo for 26 weeks (registered at ClinicalTrials.gov: NCT02621554). Baseline and follow-up assessments included the California Verbal Learning Task (CVLT, main outcome), the ModBent task, anthropometry, markers of glucose and lipid metabolism, inflammation and neurotrophins derived from fasting blood, multimodal neuroimaging at 3 and 7 T, and questionnaires to assess confounding factors.

RESULTS

Multivariate repeated-measures ANOVA did not detect significant time by group effects for CVLT performance. There was a trend for preserved pattern recognition memory after resveratrol, while performance decreased in the placebo group (n.s., p = 0.07). Further exploratory analyses showed increases in both groups over time in body fat, cholesterol, fasting glucose, interleukin 6, high sensitive C-reactive protein, tumor necrosis factor alpha and in mean diffusivity of the subiculum and presubiculum, as well as decreases in physical activity, brain-derived neurotrophic factor and insulin-like growth factor 1 at follow-up, which were partly more pronounced after resveratrol.

DISCUSSION

This interventional study failed to show significant improvements in verbal memory after 6 months of resveratrol in healthy elderly with a wide BMI range. A non-significant trend emerged for positive effects on pattern recognition memory, while possible confounding effects of unfavorable changes in lifestyle behavior, neurotrophins and inflammatory markers occurred. Our findings also indicate the feasibility to detect (un)healthy aging-related changes in measures of hippocampus microstructure after 6 months using 7T diffusion MRI. More studies incorporating a longer duration and larger sample size are needed to determine if resveratrol enhances memory performance in healthy older adults.

Impact of Resveratrol on Glucose Control, Hippocampal Structure and Connectivity, and Memory Performance in Patients with Mild Cognitive Impairment

In healthy older adults, resveratrol supplementation has been shown to improve long-term glucose control, resting-state functional connectivity (RSFC) of the hippocampus, and memory function. Here, we aimed to investigate if these beneficial effects extend to individuals at high-risk for dementia, i.e., patients with mild cognitive impairment (MCI). In a randomized, double-blind interventional study, 40 well-characterized patients with MCI (21 females; 50-80 years) completed 26 weeks of resveratrol (200 mg/d; n = 18) or placebo (1,015 mg/d olive oil; n = 22) intake. Serum levels of glucose, glycated hemoglobin A1c and insulin were determined before and after intervention. Moreover, cerebral magnetic resonance imaging (MRI) (3T) (n = 14 vs. 16) was conducted to analyze hippocampus volume, microstructure and RSFC, and neuropsychological testing was conducted to assess learning and memory (primary endpoint) at both time points. In comparison to the control group, resveratrol supplementation resulted in lower glycated hemoglobin A1c concentration with a moderate effect size (ANOVA_RMp = 0.059, Cohen's d = 0.66), higher RSFC between right anterior hippocampus and right angular cortex (p < 0.001), and led to a moderate preservation of left anterior hippocampus volume (ANOVA_RMp = 0.061, Cohen's d = 0.68). No significant differences in memory performance emerged between groups. This proof-of-concept study indicates for the first-time that resveratrol intake may reduce glycated hemoglobin A1c, preserves hippocampus volume, and improves hippocampus RSFC in at-risk patients for dementia. Larger trials with longer intervention time should now determine if these benefits can be validated and extended to cognitive function.

Non-invasive brain stimulation of the aging brain: State of the art and future perspectives

Favored by increased life expectancy and reduced birth rate, worldwide demography is rapidly shifting to older ages. The golden age of aging is not only an achievement but also a big challenge because of the load of the elderly on social and medical health care systems. Moreover, the impact of age-related decline of attention, memory, reasoning and executive functions on self-sufficiency emphasizes the need of interventions to maintain cognitive abilities at a useful degree in old age. Recently, neuroscientific research explored the chance to apply Non-Invasive Brain Stimulation (NiBS) techniques (as transcranial electrical and magnetic stimulation) to healthy aging population to preserve or enhance physiologically-declining cognitive functions. The present review will update and address the current state of the art on NiBS in healthy aging. Feasibility of NiBS techniques will be discussed in light of recent neuroimaging (either structural or functional) and neurophysiological models proposed to explain neural substrates of the physiologically aging brain. Further, the chance to design multidisciplinary interventions to maximize the efficacy of NiBS techniques will be introduced as a necessary future direction.

Altered Neural Activity during Semantic Object Memory Retrieval in Amnestic Mild Cognitive Impairment as Measured by Event-Related Potentials

Deficits in semantic memory in individuals with amnestic mild cognitive impairment (aMCI) have been previously reported, but the underlying neurobiological mechanisms remain to be clarified. We examined event-related potentials (ERPs) associated with semantic memory retrieval in 16 individuals with aMCI as compared to 17 normal controls using the Semantic Object Retrieval Task (EEG SORT). In this task, subjects judged whether pairs of words (object features) elicited retrieval of an object (retrieval trials) or not (non-retrieval trials). Behavioral findings revealed that aMCI subjects had lower accuracy scores and marginally longer reaction time compared to controls. We used a multivariate analytical technique (STAT-PCA) to investigate similarities and differences in ERPs between aMCI and control groups. STAT-PCA revealed a left fronto-temporal component starting at around 750 ms post-stimulus in both groups. However, unlike controls, aMCI subjects showed an increase in the frontal-parietal scalp potential that distinguished retrieval from non-retrieval trials between 950 and 1050 ms post-stimulus negatively correlated with the performance on the logical memory subtest of the Wechsler Memory Scale-III. Thus, individuals with aMCI were not only impaired in their behavioral performance on SORT relative to controls, but also displayed alteration in the corresponding ERPs. The altered neural activity in aMCI compared to controls suggests a more sustained and effortful search during object memory retrieval, which may be a potential marker indicating disease processes at the pre-dementia stage.

Advanced Neuroimaging Methods Towards Characterization of Early Stages of Alzheimer's Disease

In the past 5 years, imaging network properties in the brain of patients with Alzheimer's disease (AD) has revolutionized our understanding of this disorder. Postmortem data had already suggested that the damage spreads along functional neural networks, but postmortem studies do not provide information on the temporal evolution of the damage in the same patient, essential to determine spreading. These data can be provided by functional and structural neuroimaging, which allow for the visualization over time of the progressive damage inflicted by AD. Functional networks can be mapped by determining the synchrony across brain regions of the blood oxygenation level dependence (BOLD) signal on functional magnetic resonance imaging (MRI) during quiet wakefulness. Other less extensively used techniques are also useful. For instance, amyloid deposition can be imaged and its progression mapped to determine whether it follows brain networks, and, if so, which are affected earliest. Network patterns of neurobiological changes, including tau deposition, may prove critical to our understanding of the neurobiology of AD and therefore open the way for therapeutic interventions.

Investigating virtual reality navigation in amnestic mild cognitive impairment using fMRI

Spatial navigation requires a well-established network of brain regions, including the hippocampus, caudate nucleus, and retrosplenial cortex. Amnestic Mild Cognitive Impairment (aMCI) is a condition with predominantly memory impairment, conferring a high predictive risk factor for dementia. aMCI is associated with hippocampal atrophy and subtle deficits in spatial navigation. We present the first use of a functional Magnetic Resonance Imaging (fMRI) navigation task in aMCI, using a virtual reality analog of the Radial Arm Maze. Compared with controls, aMCI patients showed reduced activity in the hippocampus bilaterally, retrosplenial cortex, and left dorsolateral prefrontal cortex. Reduced activation in key areas for successful navigation, as well as additional regions, was found alongside relatively normal task performance. Results also revealed increased activity in the right dorsolateral prefrontal cortex in aMCI patients, which may reflect compensation for reduced activations elsewhere. These data support suggestions that fMRI spatial navigation tasks may be useful for staging of progression in MCI.

Effects of resveratrol on memory performance, hippocampal functional connectivity, and glucose metabolism in healthy older adults

Dietary habits such as caloric restriction or nutrients that mimic these effects may exert beneficial effects on brain aging. The plant-derived polyphenol resveratrol has been shown to increase memory performance in primates; however, interventional studies in older humans are lacking. Here, we tested whether supplementation of resveratrol would enhance memory performance in older adults and addressed potential mechanisms underlying this effect. Twenty-three healthy overweight older individuals that successfully completed 26 weeks of resveratrol intake (200 mg/d) were pairwise matched to 23 participants that received placebo (total n = 46, 18 females, 50-75 years). Before and after the intervention/control period, subjects underwent memory tasks and neuroimaging to assess volume, microstructure, and functional connectivity (FC) of the hippocampus, a key region implicated in memory functions. In addition, anthropometry, glucose and lipid metabolism, inflammation, neurotrophic factors, and vascular parameters were assayed. We observed a significant effect of resveratrol on retention of words over 30 min compared with placebo (p = 0.038). In addition, resveratrol led to significant increases in hippocampal FC, decreases in glycated hemoglobin (HbA1c) and body fat, and increases in leptin compared with placebo (all p < 0.05). Increases in FC between the left posterior hippocampus and the medial prefrontal cortex correlated with increases in retention scores and with decreases in HbA1c (all p < 0.05). This study provides initial evidence that supplementary resveratrol improves memory performance in association with improved glucose metabolism and increased hippocampal FC in older adults. Our findings offer the basis for novel strategies to maintain brain health during aging.

Pharmacokinetic and pharmacodynamic evaluation of donepezil for the treatment of Alzheimer's disease

INTRODUCTION

Donepezil is a highly selective acetylcholinesterase inhibitor and one of the only four drugs currently approved for treatment of Alzheimer's dementia. Providing high bioavailability and a very long half-time, donepezil is regarded as effective and well tolerable in Alzheimer's disease patients, even in difficult clinical conditions such as hepatic or renal impairment. It moderately improves cognitive and global functioning scores in patients with mild to moderate Alzheimer's disease over the course of 6 - 12 months, with open-label extension studies suggesting effects of even longer duration.

AREAS COVERED

We summarized relevant pharmacokinetic, pharmacodynamic, clinical trial and neuroimaging data of donepezil. A literature search was performed in the PubMed database; articles published until October 2013 have been considered for this review. Moreover, references from original work and reviews have been searched for further relevant literature.

EXPERT OPINION

Donepezil is one of the most frequently prescribed anti-dementia drugs. The recent additional approval of the 23 mg formulation will expand its use in patients with moderate to severe Alzheimer's disease. After numerous Phase III study failures of novel disease-modifying drugs for Alzheimer's disease, donepezil is likely going to stay a first-line therapeutic option in Alzheimer's disease in the upcoming years.

Whole cortical and default mode network mean functional connectivity as potential biomarkers for mild Alzheimer's disease

The search for an Alzheimer's disease (AD) biomarker is one of the most relevant contemporary research topics due to the high prevalence and social costs of the disease. Functional connectivity (FC) of the default mode network (DMN) is a plausible candidate for such a biomarker. We evaluated 22 patients with mild AD and 26 age- and gender-matched healthy controls. All subjects underwent resting functional magnetic resonance imaging (fMRI) in a 3.0 T scanner. To identify the DMN, seed-based FC of the posterior cingulate was calculated. We also measured the sensitivity/specificity of the method, and verified a correlation with cognitive performance. We found a significant difference between patients with mild AD and controls in average z-scores: DMN, whole cortical positive (WCP) and absolute values. DMN individual values showed a sensitivity of 77.3% and specificity of 70%. DMN and WCP values were correlated to global cognition and episodic memory performance. We showed that individual measures of DMN connectivity could be considered a promising method to differentiate AD, even at an early phase, from normal aging. Further studies with larger numbers of participants, as well as validation of normal values, are needed for more definitive conclusions.

The APOE ɛ4 allele affects complexity and functional connectivity of resting brain activity in healthy adults

The apolipoprotein E (APOE) gene is associated with structural and functional brain changes. We have used multiscale entropy (MSE) analysis to detect changes in the complexity of resting blood oxygen level-dependent (BOLD) signals associated with aging and cognitive function. In this study, we further hypothesized that the APOE genotype may affect the complexity of spontaneous BOLD activity in younger and older adults, and such altered complexity may be associated with certain changes in functional connectivity. We conducted a resting-state functional magnetic resonance imaging experiment in a cohort of 100 younger adults (aged 20-39 years; mean 27.2 ± 4.3 years; male/female: 53/47) and 112 older adults (aged 60-79 years; mean 68.4 ± 6.5 years; male/female: 54/58), and applied voxelwise MSE analysis to assess the main effect of APOE genotype on resting-state BOLD complexity and connectivity. Although the main effect of APOE genotype on BOLD complexity was not observed in younger group, we observed that older APOE ɛ4 allele carriers had significant reductions in BOLD complexity in precuneus and posterior cingulate regions, relative to noncarriers. We also observed that reduced BOLD complexity in precuneus and posterior cingulate regions was associated with increased functional connectivity to the superior and inferior frontal gyrus in the older group. These results support the compensatory recruitment hypothesis in older APOE ɛ4 carriers, and confer the impact of the APOE genotype on the temporal dynamics of brain activity in older adults.

Modular reorganization of brain resting state networks and its independent validation in Alzheimer's disease patients

Previous studies have demonstrated disruption in structural and functional connectivity occurring in the Alzheimer's Disease (AD). However, it is not known how these disruptions alter brain network reorganization. With the modular analysis method of graph theory, and datasets acquired by the resting-state functional connectivity MRI (R-fMRI) method, we investigated and compared the brain organization patterns between the AD group and the cognitively normal control (CN) group. Our main finding is that the largest homotopic module (defined as the insula module) in the CN group was broken down to the pieces in the AD group. Specifically, it was discovered that the eight pairs of the bilateral regions (the opercular part of inferior frontal gyrus, area triangularis, insula, putamen, globus pallidus, transverse temporal gyri, superior temporal gyrus, and superior temporal pole) of the insula module had lost symmetric functional connection properties, and the corresponding gray matter concentration (GMC) was significant lower in AD group. We further quantified the functional connectivity changes with an index (index A) and structural changes with the GMC index in the insula module to demonstrate their great potential as AD biomarkers. We further validated these results with six additional independent datasets (271 subjects in six groups). Our results demonstrated specific underlying structural and functional reorganization from young to old, and for diseased subjects. Further, it is suggested that by combining the structural GMC analysis and functional modular analysis in the insula module, a new biomarker can be developed at the single-subject level.

Therapeutic strategies for tau mediated neurodegeneration

Based on the amyloid hypothesis, controlling β-amyloid protein (Aβ) accumulation is supposed to suppress downstream pathological events, tau accumulation, neurodegeneration and cognitive decline. However, in recent clinical trials, Aβ removal or reducing Aβ production has shown limited efficacy. Moreover, while active immunisation with Aβ resulted in the clearance of Aβ, it did not prevent tau pathology or neurodegeneration. This prompts the concern that it might be too late to employ Aβ targeting therapies once tau mediated neurodegeneration has occurred. Therefore, it is timely and very important to develop tau directed therapies. The pathomechanisms of tau mediated neurodegeneration are unclear but hyperphosphorylation, oligomerisation, fibrillisation and propagation of tau pathology have been proposed as the likely pathological processes that induce loss of function or gain of toxic function of tau, causing neurodegeneration. Here we review the strategies for tau directed treatments based on recent progress in research on tau and our understanding of the pathomechanisms of tau mediated neurodegeneration.

Altered functional connectivity in an aged rat model of postoperative cognitive dysfunction: a study using resting-state functional MRI

Background

Postoperative cognitive impairment is a common complication after cardiac and major non-cardiac surgery in the elderly, but its causes and mechanisms remain unclear. The purpose of the current study was to use resting-state functional magnetic resonance imaging (fMRI) to explore changes in the functional connectivity, i.e. the synchronization of low frequency fluctuation (LFF), in an animal model of cognitive impairment in aged rats.

Methods

Aged (22 months) rats were anaesthetized with 40 µg/kg fentanyl and 500 µg/kg droperidol (intraperitoneal) for splenectomy. Cognitive function was assessed using Y maze prior to operation and on postoperative days 1, 3 and 9. To evaluate functional connectivity, resting-state fMRI data were acquired using a 3T MR imaging system with a 4 channel phase array rat head coil.

Results

Cognitive function was impaired at postoperative days 1 and 3 compared with preoperative. Significant synchronized LFF was detected bilaterally in the primary somatosensory cortex and hippocampus preoperatively. By contrast, no significant LFF synchronization was detected in the right primary somatosensory cortex and right hippocampus on postoperative days 1 and 3, although the pattern of functional connectivity had become almost normal by day 9.

Conclusion

Splenectomy performed under neuroleptic anaesthesia triggers a cognitive decline that is associated with altered spontaneous neuronal activity in the cortex and hippocampus.

Meta-analysis of functional network alterations in Alzheimer's disease: toward a network biomarker

The increasing prevalence of Alzheimer's disease (AD) emphasizes the need for sensitive biomarkers. Memory, a core deficit in AD, involves the interaction of distributed brain networks. We propose that biomarkers should be sought at the level of disease-specific disturbances in large-scale neural networks instead of alterations in a single brain region. This is the first voxel-level quantitative meta-analysis of default mode connectivity and task-related activation in 1196 patients and 1255 controls to detect robust changes in components of large-scale neural networks. We show that with disease progression, specific components of networks are widespread altered. The medial parietal regions and the subcortical areas are differentially affected depending on the disease stage. Specific compensatory mechanisms are only seen in the earliest stages, before symptoms are evident, and could become a functional network biomarker or target for interventions. These results underline the need to further fine-grain these networks spatially and temporally across disease stages. To conclude, AD should indeed be considered as a syndrome involving neural network disruption before cognitive deficits are detectable.

Resting-state functional connectivity in normal brain aging

The world is aging and, as the elderly population increases, age-related cognitive decline emerges as a major concern. Neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), allow the investigation of the neural bases of age-related cognitive changes in vivo. Typically, fMRI studies map brain activity while subjects perform cognitive tasks, but such paradigms are often difficult to implement on a wider basis. Resting-state fMRI (rs-fMRI) has emerged as an important alternative modality of fMRI data acquisition, during which no specific task is required. Due to such simplicity and the reliability of rs-fMRI data, this modality presents increased feasibility and potential for clinical application in the future. With rs-fMRI, fluctuations in regional brain activity can be detected across separate brain regions and the patterns of intercorrelation between the functioning of these regions are measured, affording quantitative indices of resting-state functional connectivity (RSFC). This review article summarizes the results of recent rs-fMRI studies that have documented a variety of aging-related RSFC changes in the human brain, discusses the neurophysiological hypotheses proposed to interpret such findings, and provides an overview of the future, highly promising perspectives in this field.

Functional biomarkers for neurodegenerative disorders based on the network paradigm

This commentary provides a brief introduction to the various uses that functional neuroimaging biomarkers can play in detecting, diagnosing, assessing treatment response and investigating neurodegenerative disorders. It then goes on to explain why the emphasis of much recent work has shifted to network-based biomarkers, as opposed to those that examine individual brain regions. A number of examples are referenced that illustrate the points made.

The future of Alzheimer's disease: the next 10 years

Alzheimer's disease (AD) is a fast growing world-wide epidemic. AD is a genetically complex, slowly progressive, and irreversible neurodegenerative disease of the brain. During decades of asymptomatic progression multiple interactive systems, pathways and molecular mechanisms (e.g. protein processing, aberrant signaling, inflammation and immune system, lipid transport, endocytosis, apoptosis, oxidative damage and response to stress, tau pathology, neuron and synapse loss, energy metabolism), contribute to the development of the early clinical prodromal stage with episodic memory deficits and to further decline and loss of general cognitive functioning during the final syndromal dementia stage. The non-mendelian genetically complex "sporadic" AD type is the most common form of dementia affecting people usually over the age of 65. Despite considerable progress of AD research in recent years and evolving paradigm shifts in both pathophysiological concepts as well as in diagnostic criteria fundamental challenges have not yet been resolved. The strong age-related incidence, the recent failure and complete lack of disease-modifying or preventive therapy that may delay onset or substantially affect the pathophysiology of AD, result in an enormous burden posed both on individuals, their families and care givers, and the societies at large, and these call for urgent concerted worldwide measures. Based on the meeting of the German Task Force on Alzheimer's Disease (GTF-AD) in Paris on July 19th 2011, the present position paper provides an overview on the current state and future developments in epidemiology, pathophysiology, disease conceptualization, diagnostic criteria and their use in research and clinical practice, as well as preventive and symptomatic therapeutic approaches. Particular emphasis is placed on a discussion of the different approaches to diagnostics and therapy taken by preventive/public health medicine, methodologically advanced academic research propagating the use of sophisticated biomarkers, and everyday clinical practice focusing on patient-centered care. During the next 10 years, major advances both in early detection as well as in therapy and comprehensive AD care seem mandatory. These still unmet needs call for ever more concerted and focused efforts in research across the world to combat the erupting and as yet uncontrolled epidemic of AD.