Resting State Electrophysiological Profiles and Their Relationship with Cognitive Performance in Cognitively Unimpaired Older Adults: A Systematic Review.

Background: Aging is a complex and natural process. The physiological decline related to aging is accompanied by a slowdown in cognitive processes, which begins shortly after individuals reach maturity. These changes have been sometimes interpreted as a compensatory sign and others as a fingerprint of deterioration. Objective: In this context, our aim is to uncover the mechanisms that underlie and support normal cognitive functioning in the brain during the later stages of life. Methods: With this purpose, a systematic literature search was conducted using PubMed, Scopus, and Web of Science databases, which identified 781 potential articles. After applying inclusion and exclusion criteria, we selected 12 studies that examined the brain oscillations patterns in resting-state conditions associated with cognitive performance in cognitively unimpaired older adults. Results: Although cognitive healthy aging was characterized differently across studies, and various approaches to analyzing brain activity were employed, our review indicates a relationship between alpha peak frequency (APF) and improved performance in neuropsychological scores among cognitively unimpaired older adults. Conclusions: A higher APF is linked with a higher score in intelligence, executive function, and general cognitive performance, and could be considered an optimal, and easy-to-assess, electrophysiological marker of cognitive health in older adults.

When Maturation is Not Linear: Brain Oscillatory Activity in the Process of Aging as Measured by Electrophysiology.

Changes in brain oscillatory activity are commonly used as biomarkers both in cognitive neuroscience and in neuropsychiatric conditions. However, little is known about how its profile changes across maturation. Here we use regression models to characterize magnetoencephalography power changes within classical frequency bands in a sample of 792 healthy participants, covering the range 13 to 80 years old. Our findings unveil complex, non-linear power trajectories that defy the traditional linear paradigm, with notable cortical region variations. Interestingly, slow wave activity increases correlate with improved cognitive performance throughout life and larger gray matter volume in the elderly. Conversely, fast wave activity diminishes in adulthood. Elevated low-frequency activity during aging, traditionally seen as compensatory, may also signify neural deterioration. This dual interpretation, highlighted by our study, reveals the intricate dynamics between brain oscillations, cognitive performance, and aging. It advances our understanding of neurodevelopment and aging by emphasizing the regional specificity and complexity of brain rhythm changes, with implications for cognitive and structural integrity.

MEG Oscillatory Slowing in Cognitive Impairment is Associated with the Presence of Subjective Cognitive Decline.

The mechanisms behind Alzheimer's disease are not yet fully described, and changes in the electrophysiology of patients across the continuum of the disease could help to understand them. In this work, we study the power spectral distribution of a set of 129 individuals from the Connectomics of Brian Aging and Dementia project.From this sample, we acquired task-free data, with eyes closed, and estimated the power spectral distribution in source space. We compared the spectral profiles of three groups of individuals: 70 healthy controls, 27 patients with amnestic MCI, and 32 individuals showing cognitive impairment without subjective complaints (IWOC).The results showed a slowing of the brain activity in the aMCI patients, when compared to both the healthy controls and the IWOC individuals. These differences appeared both as a decrease in power for high frequency oscillations and an increase in power in alpha oscillations. The slowing of the spectrum was significant mainly in parietal and medial frontal areas.We were able to validate the slowing of the brain activity in individuals with aMCI, appearing in our sample in areas related to the default mode network. However, this pattern did not appear in the IWOC individuals, suggesting that their condition is not part of the AD continuum. This work raises interesting questions about this group of individuals, and the underlying brain mechanisms behind their cognitive impairment.

Cognitive Training Modulates Brain Hypersynchrony in a Population at Risk for Alzheimer's Disease.

BACKGROUND: Recent studies demonstrated that brain hypersynchrony is an early sign of dysfunction in Alzheimer's disease (AD) that can represent a proxy for clinical progression. Conversely, non-pharmacological interventions, such as cognitive training (COGTR), are associated with cognitive gains that may be underpinned by a neuroprotective effect on brain synchrony. OBJECTIVE: To study the potential of COGTR to modulate brain synchrony and to eventually revert the hypersynchrony phenomenon that characterizes preclinical AD. METHODS: The effect of COGTR was examined in a sample of healthy controls (HC, n = 41, 22 trained) and individuals with subjective cognitive decline (SCD, n = 49, 24 trained). Magnetoencephalographic activity and neuropsychological scores were acquired before and after a ten-week COGTR intervention aimed at improving cognitive function and daily living performance. Functional connectivity (FC) was analyzed using the phase-locking value. A mixed-effects ANOVA model with factors time (pre-intervention/post-intervention), training (trained/non-trained), and diagnosis (HC/SCD) was used to investigate significant changes in FC. RESULTS: We found an average increase in alpha-band FC over time, but the effect was different in each group (trained and non-trained). In the trained group (HC and SCD), we report a reduction in the increase in FC within temporo-parietal and temporo-occipital connections. In the trained SCD group, this reduction was stronger and showed a tentative correlation with improved performance in different cognitive tests. CONCLUSION: COGTR interventions could mitigate aberrant increases in FC in preclinical AD, promoting brain synchrony normalization in groups at a higher risk of developing dementia.

Sex Differences in Magnetoencephalography-Identified Functional Connectivity in the Human Connectome Project Connectomics of Brain Aging and Dementia Cohort.

Introduction: The human brain shows modest traits of sexual dimorphism, with the female brain, on average, 10% smaller than the male brain. These differences do not imply a lowered cognitive performance, but suggest a more optimal brain organization in women. Here we evaluate the patterns of functional connectivity (FC) in women and men from the Connectomics of Brain Aging and Dementia sample. Methods: We used phase locking values to calculate FC from the magnetoencephalography time series in a sample of 138 old adults (87 females and 51 males). We compared the FC patterns between sexes, with the intention of detecting regions with different levels of connectivity. Results: We found a frontal cluster, involving anterior cingulate and the medial frontal lobe, where women showed higher FC values than men. Involved connections included the following: (1) medial parietal areas, such as posterior cingulate cortices and precunei; (2) right insula; and (3) medium cingulate and paracingulate cortices. Moreover, these differences persisted when considering only cognitively intact individuals, but not when considering only cognitively impaired individuals. Discussion: Increased anteroposterior FC has been identified as a biomarker for increased risk of developing cognitive impairment or dementia. In our study, cognitively intact women showed higher levels of FC than their male counterparts. This result suggests that neurodegenerative processes could be taking place in these women, but the changes are undetected by current diagnosis tools. FC, as measured here, might be valuable for early identification of this neurodegeneration.

Neurocognitive Impairment in Severe Mental Illness. Comparative study with Spanish Speaking Patients.

BACKGROUND: Serious mental illness (SMI) represents a category of psychiatric disorders characterized by specific difficulties of personal and social functioning, derived from suffering severe and persistent mental health problems. AIMS: We wanted to look into differences in cognitive performance among different SMI patients. METHODS: Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) screening was applied in one sample of SMI patients (n = 149) and another of healthy comparison participants (n = 35). Within the SMI sample, three different subsamples were formed: one with 97 patients with schizophrenia, a second with 29 patients with mood disorders, and a third with 23 patients with personality disorder. We performed a comparative study within and between groups. RESULTS: Analysis of covariance was performed. Significant differences were found for cognitive functioning including attention and memory. CONCLUSIONS: RBANS can be recommended for the detection of neurocognitive deficits in psychiatric disorders, especially in Schizophrenia.

Ongoing Oscillatory Electrophysiological Alterations in Frail Older Adults: A MEG Study.

Objective: The role of the central nervous system in the pathophysiology of frailty is controversial. We used magnetoencephalography (MEG) to search for abnormalities in the ongoing oscillatory neural activity of frail individuals without global cognitive impairment. Methods: Fifty four older (≥70 years) and cognitively healthy (Mini-Mental State Examination ≥24) participants were classified as robust (0 criterion, n = 34) or frail (≥ 3 criteria, n = 20) following Fried's phenotype. Memory, language, attention, and executive function were assessed through well-validated neuropsychological tests. Every participant underwent a resting-state MEG and a T1-weighted magnetic resonance imaging scan. We performed MEG power spectral analyses to compare the electrophysiological profiles of frail and robust individuals. We used an ensemble learner to investigate the ability of MEG spectral power to discriminate frail from robust participants. Results: We identified increased relative power in the frail group in the mu (p < 0.05) and sensorimotor (p < 0.05) frequencies across right sensorimotor, posterior parietal, and frontal regions. The ensemble learner discriminated frail from robust participants [area under the curve = 0.73 (95% CI = 0.49-0.98)]. Frail individuals performed significantly worse in the Trail Making Test, Digit Span Test (forward), Rey-Osterrieth Complex Figure, and Semantic Fluency Test. Interpretation: Frail individuals without global cognitive impairment showed ongoing oscillatory alterations within brain regions associated with aspects of motor control, jointly to failures in executive function. Our results suggest that some physical manifestations of frailty might partly arise from failures in central structures relevant to sensorimotor and executive processing.

Permutation Entropy and Statistical Complexity in Mild Cognitive Impairment and Alzheimer's Disease: An Analysis Based on Frequency Bands.

We present one of the first applications of Permutation Entropy (PE) and Statistical Complexity (SC) (measured as the product of PE and Jensen-Shanon Divergence) on Magnetoencephalography (MEG) recordings of 46 subjects suffering from Mild Cognitive Impairment (MCI), 17 individuals diagnosed with Alzheimer's Disease (AD) and 48 healthy controls. We studied the differences in PE and SC in broadband signals and their decomposition into frequency bands ( δ , θ , α and ß ), considering two modalities: (i) raw time series obtained from the magnetometers and (ii) a reconstruction into cortical sources or regions of interest (ROIs). We conducted our analyses at three levels: (i) at the group level we compared SC in each frequency band and modality between groups; (ii) at the individual level we compared how the [PE, SC] plane differs in each modality; and (iii) at the local level we explored differences in scalp and cortical space. We recovered classical results that considered only broadband signals and found a nontrivial pattern of alterations in each frequency band, showing that SC does not necessarily decrease in AD or MCI.

Age and APOE genotype affect the relationship between objectively measured physical activity and power in the alpha band, a marker of brain disease.

BACKGROUND: Electrophysiological studies show that reductions in power within the alpha band are associated with the Alzheimer's disease (AD) continuum. Physical activity (PA) is a protective factor that has proved to reduce AD risk and pathological brain burden. Previous research has confirmed that exercise increases power in the alpha range. However, little is known regarding whether other non-modifiable risk factors for AD, such as increased age or APOE ε4 carriage, alter the association between PA and power in the alpha band. METHODS: The relationship between PA and alpha band power was examined in a sample of 113 healthy adults using magnetoencephalography. Additionally, we explored whether ε4 carriage and age modulate this association. The correlations between alpha power and gray matter volumes and cognition were also investigated. RESULTS: We detected a parieto-occipital cluster in which PA positively correlated with alpha power. The association between PA and alpha power remained following stratification of the cohort by genotype. Younger and older adults were investigated separately, and only younger adults exhibited a positive relationship between PA and alpha power. Interestingly, when four groups were created based on age (younger-older adult) and APOE (E3/E3-E3/E4), only younger E3/E3 (least predicted risk) and older E3/E4 (greatest predicted risk) had associations between greater alpha power and higher PA. Among older E3/E4, greater alpha power in these regions was associated with improved memory and preserved brain structure. CONCLUSION: PA could protect against the slowing of brain activity that characterizes the AD continuum, where it is of benefit for all individuals, especially E3/E4 older adults.

Functional Connectivity Disruption in Frail Older Adults Without Global Cognitive Deficits.

Frailty is a common representation of cumulative age-related decline that may precede disability in older adults. In our study, we used magnetoencephalography (MEG) to explore the existence of abnormalities in the synchronization patterns of frail individuals without global cognitive impairment. Fifty-four older (≥70 years) and cognitively healthy (Mini-Mental State Examination ≥24) adults, 34 robust (not a single positive Fried criterion) and 20 frail (≥3 positive Fried criteria) underwent a resting-state MEG recording and a T1-weighted magnetic resonance imaging scan. Seed-based functional connectivity (FC) analyses were used to explore group differences in the synchronization of fronto-parietal areas relevant to motor function. Additionally, we performed group comparisons of intra-network FC for key resting-state networks such as the sensorimotor, fronto-parietal, default mode, and attentional (dorsal and ventral) networks. Frail participants exhibited reduced FC between posterior regions of the parietal cortex (bilateral supramarginal gyrus, right superior parietal lobe, and right angular gyrus) and widespread clusters spanning mainly fronto-parietal regions. Frail participants also demonstrated reduced intra-network FC within the fronto-parietal, ventral attentional, and posterior default mode networks. All the FC results concerned the upper beta band, a frequency range classically linked to motor function. Overall, our findings reveal the existence of abnormalities in the synchronization patterns of frail individuals within central structures important for accurate motor control. This study suggests that alterations in brain connectivity might contribute to some motor impairments associated with frailty.

The relationship between physical activity, apolipoprotein E ε4 carriage, and brain health.

BACKGROUND: Neuronal hyperexcitability and hypersynchrony have been described as key features of neurophysiological dysfunctions in the Alzheimer's disease (AD) continuum. Conversely, physical activity (PA) has been associated with improved brain health and reduced AD risk. However, there is controversy regarding whether AD genetic risk (in terms of APOE ε4 carriage) modulates these relationships. The utilization of multiple outcome measures within one sample may strengthen our understanding of this complex phenomenon. METHOD: The relationship between PA and functional connectivity (FC) was examined in a sample of 107 healthy older adults using magnetoencephalography. Additionally, we explored whether ε4 carriage modulates this association. The correlation between FC and brain structural integrity, cognition, and mood was also investigated. RESULTS: A relationship between higher PA and decreased FC (hyposynchrony) in the left temporal lobe was observed among all individuals (across the whole sample, in ε4 carriers, and in ε4 non-carriers), but its effects manifest differently according to genetic risk. In ε4 carriers, we report an association between this region-specific FC profile and preserved brain structure (greater gray matter volumes and higher integrity of white matter tracts). In this group, decreased FC also correlated with reduced anxiety levels. In ε4 non-carriers, this profile is associated with improved cognition (working and episodic memory). CONCLUSIONS: PA could mitigate the increase in FC (hypersynchronization) that characterizes preclinical AD, being beneficial for all individuals, especially ε4 carriers.

Complexity changes in preclinical Alzheimer's disease: An MEG study of subjective cognitive decline and mild cognitive impairment.

OBJECTIVE: To analyse magnetoencephalogram (MEG) signals with Lempel-Ziv Complexity (LZC) to identify the regions of the brain showing changes related to cognitive decline and Alzheimers Disease (AD). METHODS: LZC was used to study MEG signals in the source space from 99 participants (36 male, 63 female, average age: 71.82 ± 4.06) in three groups (33 subjects per group): healthy (control) older adults, older adults with subjective cognitive decline (SCD), and adults with mild cognitive impairment (MCI). Analyses were performed in broadband (2-45 Hz) and in classic narrow bands (theta (4-8 Hz), alpha (8-12 Hz), low beta (12-20 Hz), high beta (20-30 Hz), and, gamma (30-45 Hz)). RESULTS: LZC was significantly lower in subjects with MCI than in those with SCD. Moreover, subjects with MCI had significantly lower MEG complexity than controls and SCD subjects in the beta frequency band. Lower complexity was correlated with smaller hippocampal volumes. CONCLUSIONS: Brain complexity - measured with LZC - decreases in MCI patients when compared to SCD and healthy controls. This decrease is associated with a decrease in hippocampal volume, a key feature in AD progression. SIGNIFICANCE: This is the first study to date characterising the changes of brain activity complexity showing the specific spatial pattern of the alterations as well as the morphological correlations throughout preclinical stages of AD.

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.

Biomagnetic biomarkers for dementia: A pilot multicentre study with a recommended methodological framework for magnetoencephalography.

INTRODUCTION: An increasing number of studies are using magnetoencephalography (MEG) to study dementia. Here we define a common methodological framework for MEG resting-state acquisition and analysis to facilitate the pooling of data from different sites. METHODS: Two groups of patients with mild cognitive impairment (MCI, n = 84) and healthy controls (n = 84) were combined from three sites, and site and group differences inspected in terms of power spectra and functional connectivity. Classification accuracy for MCI versus controls was compared across three different types of MEG analyses, and compared with classification based on structural MRI. RESULTS: The spectral analyses confirmed frequency-specific differences in patients with MCI, both in power and connectivity patterns, with highest classification accuracy from connectivity. Critically, site acquisition differences did not dominate the results. DISCUSSION: This work provides detailed protocols and analyses that are sensitive to cognitive impairment, and that will enable standardized data sharing to facilitate large-scale collaborative projects.

Electrophysiological brain signatures for the classification of subjective cognitive decline: towards an individual detection in the preclinical stages of dementia.

BACKGROUND: Alzheimer's disease (AD) prevalence is rapidly growing as worldwide populations grow older. Available treatments have failed to slow down disease progression, thus increasing research focus towards early or preclinical stages of the disease. Subjective cognitive decline (SCD) is known to increase the risk of developing AD and several other negative outcomes. However, it is still very scarcely characterized and there is no neurophysiological study devoted to its individual classification which could improve targeted sample recruitment for clinical trials. METHODS: Two hundred fifty-two older adults (70 healthy controls, 91 SCD, and 91 MCI) underwent a magnetoencephalography scan. Alpha relative power in the source space was employed to train a LASSO classifier and applied to distinguish between healthy controls and SCD. Moreover, MCI participants were used to further validate the previously trained algorithm. RESULTS: The classifier was significantly associated to SCD with an AUC of 0.81 in the whole sample. After randomly splitting the sample in 2/3 for discovery and 1/3 for validation, the newly trained classifier was also able to correctly classify SCD individuals with an AUC of 0.75 in the validation sample. The regions selected by the algorithm included medial frontal, temporal, and occipital areas. The algorithm trained to select SCD individuals was also significantly associated to MCI diagnostic. CONCLUSIONS: According to our results, magnetoencephalography could be a useful tool for distinguishing individuals with SCD and healthy older adults without cognitive concerns. Furthermore, our classifier showed good external validity, being not only successful for an unseen SCD sample, but also in a different population with MCI cases. This supports its utility in the context of preclinical dementia. These findings highlight the potential applications of electrophysiological techniques to improve sample recruitment at the individual level in the context of clinical trials.

Sex Differences in the Complexity of Healthy Older Adults' Magnetoencephalograms.

The analysis of resting-state brain activity recording in magnetoencephalograms (MEGs) with new algorithms of symbolic dynamics analysis could help obtain a deeper insight into the functioning of the brain and identify potential differences between males and females. Permutation Lempel-Ziv complexity (PLZC), a recently introduced non-linear signal processing algorithm based on symbolic dynamics, was used to evaluate the complexity of MEG signals in source space. PLZC was estimated in a broad band of frequencies (2-45 Hz), as well as in narrow bands (i.e., theta (4-8 Hz), alpha (8-12 Hz), low beta (12-20 Hz), high beta (20-30 Hz), and gamma (30-45 Hz)) in a sample of 98 healthy elderly subjects (49 males, 49 female) aged 65-80 (average age of 72.71 ± 4.22 for males and 72.67 ± 4.21 for females). PLZC was significantly higher for females than males in the high beta band at posterior brain regions including the precuneus, and the parietal and occipital cortices. Further statistical analyses showed that higher complexity values over highly overlapping regions than the ones mentioned above were associated with larger hippocampal volumes only in females. These results suggest that sex differences in healthy aging can be identified from the analysis of magnetoencephalograms with novel signal processing methods.

Scoping Review of Neuroimaging Studies Investigating Frailty and Frailty Components.

Background: Neuroimaging techniques are a cornerstone for diagnosing and investigating cognitive decline and dementia in the elderly. In frailty research, the physical as opposed to the cognitive domain of the aging process, neuroimaging studies are less common. Here we systematically review the use of neuroimaging techniques in frailty research. Methods: We searched PUBMED for any publication reporting the association between neuroimaging markers and frailty, following Fried's original definition, as well as its determining phenotypes: gait speed, grip strength, fatigue and recent weight loss in the non-diseased population older than 65 years. Results: The search returned a total of 979 abstracts which were independently screened by 3 reviewers. In total, 17 studies met the inclusion criteria. Of these, 12 studies evaluated gait speed, 2 grip strength, and 3 frailty (2 Fried Frailty, 1 Frailty Index). An association between increased burden of white matter lesions, lower fractional anisotropy, and higher diffusivity has been associated consistently to frailty and worse performance in the different frailty components. Conclusions: White matter lesions were significantly associated to frailty and frailty components thus highlighting the potential utility of neuroimaging in unraveling the underlying mechanisms of this state. However, considering small sample size and design effects, it is not possible to completely rule out reverse causality between frailty and neuroimaging findings. More studies are needed to clarify this important clinical question.

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.

Functional brain networks reveal the existence of cognitive reserve and the interplay between network topology and dynamics.

We investigated how the organization of functional brain networks was related to cognitive reserve (CR) during a memory task in healthy aging. We obtained the magnetoencephalographic functional networks of 20 elders with a high or low CR level to analyse the differences at network features. We reported a negative correlation between synchronization of the whole network and CR, and observed differences both at the node and at the network level in: the average shortest path and the network outreach. Individuals with high CR required functional networks with lower links to successfully carry out the memory task. These results may indicate that those individuals with low CR level exhibited a dual pattern of compensation and network impairment, since their functioning was more energetically costly to perform the task as the high CR group. Additionally, we evaluated how the dynamical properties of the different brain regions were correlated to the network parameters obtaining that entropy was positively correlated with the strength and clustering coefficient, while complexity behaved conversely. Consequently, highly connected nodes of the functional networks showed a more stochastic and less complex signal. We consider that network approach may be a relevant tool to better understand brain functioning in aging.