Memory-related EEG power and coherence reductions in mild Alzheimer's disease

Electrical brain networks before and after transcranial pulsed shockwave stimulation in Alzheimer's patients

Alzheimer's disease (AD) is a neurodegenerative disorder that dramatically affects cognitive abilities and represents the most common cause of dementia. Currently, pharmacological interventions represent the main treatment to deal with the symptoms of AD; however, alternative approaches are readily sought. Transcranial pulse stimulation (TPS) is an emerging non-invasive neuromodulation technique that uses short, repetitive shockwaves with the potential to provide a wide range of vascular, metabolic, and neurotrophic changes and that has recently been shown to improve cognitive abilities in AD. This exploratory study aims to gain insight into the neurophysiological effect of one session of TPS in AD as reflected in electroencephalographic measures, e.g., spectral power, coherence, Tsallis entropy (TE), and cross-frequency coupling (cfc). We document changes in power (frontal and occipital), coherence (frontal, occipital and temporal), and TE (temporal and frontal) as well as changes in cfc (parietal-frontal, parietal-temporal, frontal-temporal). Our results emphasize the role of electroencephalographic measures as prospective markers for the neurophysiological effect of TPS.

Coherence in event-related EEG oscillations in patients with Alzheimer's disease dementia and amnestic mild cognitive impairment

Objectives Working memory performances are based on brain functional connectivity, so that connectivity may be deranged in individuals with mild cognitive impairment (MCI) and patients with dementia due to Alzheimer's disease (ADD). Here we tested the hypothesis of abnormal functional connectivity as revealed by the imaginary part of coherency (ICoh) at electrode pairs from event-related electroencephalographic oscillations in ADD and MCI patients. Methods The study included 43 individuals with MCI, 43 with ADD, and 68 demographically matched healthy controls (HC). Delta, theta, alpha, beta, and gamma bands event-related ICoh was measured during an oddball paradigm. Inter-hemispheric, midline, and intra-hemispheric ICoh values were compared in ADD, MCI, and HC groups. Results The main results of the present study can be summarized as follows: (1) A significant increase of midline frontal and temporal theta coherence in the MCI group as compared to the HC group; (2) A significant decrease of theta, delta, and alpha intra-hemispheric coherence in the ADD group as compared to the HC and MCI groups; (3) A significant decrease of theta midline coherence in the ADD group as compared to the HC and MCI groups; (4) Normal inter-hemispheric coherence in the ADD and MCI groups. Conclusions Compared with the MCI and HC, the ADD group showed disrupted event-related intra-hemispheric and midline low-frequency band coherence as an estimate of brain functional dysconnectivity underlying disabilities in daily living. Brain functional connectivity during attention and short memory demands is relatively resilient in elderly subjects even with MCI (with preserved abilities in daily activities), and it shows reduced efficiency at multiple operating oscillatory frequencies only at an early stage of ADD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-022-09920-0.

Reducing Stress with Yoga: A Systematic Review Based on Multimodal Biosignals

Stress is an enormous concern in our culture because it is the root cause of many health issues. Yoga asanas and mindfulness-based practices are becoming increasingly popular for stress management; nevertheless, the biological effect of these practices on stress reactivity is still a research domain. The purpose of this review is to emphasize various biosignals that reflect stress reduction through various yoga-based practices. A comprehensive synthesis of numerous prior investigations in the existing literature was conducted. These investigations undertook a thorough examination of numerous biosignals. Various features are extracted from these signals, which are further explored to reflect the effectiveness of yoga practice in stress reduction. The multifaceted character of stress and the extensive research undertaken in this field indicate that the proposed approach would rely on multiple modalities. The notable growth of the body of literature pertaining to prospective yoga processes is deserving of attention; nonetheless, there exists a scarcity of research undertaken on these mechanisms. Hence, it is recommended that future studies adopt more stringent yoga methods and ensure the incorporation of suitable participant cohorts.

Increased neurocardiological interplay after mindfulness meditation: a brain oscillation-based approach

Background

Brain oscillations facilitate interaction within the brain network and between the brain and heart activities, and the alpha wave, as a prominent brain oscillation, plays a major role in these coherent activities. We hypothesize that mindfully breathing can make the brain and heart activities more coherent in terms of increased connectivity between the electroencephalogram (EEG) and electrocardiogram (ECG) signals.

Methods

Eleven participants (28-52 years) attended 8 weeks of Mindfulness Based Stress Reduction (MBSR) training. EEG and ECG data of two states of mindful breathing and rest, both eye-closed, were recorded before and after the training. EEGLAB was used to analyze the alpha band (8-12 Hz) power, alpha peak frequency (APF), peak power and coherence. FMRIB toolbox was used to extract the ECG data. Heart coherence (HC) and heartbeat evoked potential (HEP) were calculated for further correlation analysis.

Results

After 8 weeks of MBSR training, the correlation between APF and HC increased significantly in the middle frontal region and bilateral temporal regions. The correlation between alpha coherence and heart coherence had similar changes, while alpha peak power did not reflect such changes. In contrast, spectrum analysis alone did not show difference before and after MBSR training.

Conclusion

The brain works in rhythmic oscillation, and this rhythmic connection becomes more coherent with cardiac activity after 8 weeks of MBSR training. Individual APF is relatively stable and its interplay with cardiac activity may be a more sensitive index than power spectrum by monitoring the brain-heart connection. This preliminary study has important implications for the neuroscientific measurement of meditative practice.

Age-Related Modifications of Electroencephalogram Coherence in Mice Models of Alzheimer's Disease and Amyotrophic Lateral Sclerosis

Evident similarities in pathological features in aging and Alzheimer's disease (AD) raise the question of a role for natural age-related adaptive mechanisms in the prevention/elimination of disturbances in interrelations between different brain areas. In our previous electroencephalogram (EEG) studies on 5xFAD- and FUS-transgenic mice, as models of AD and amyotrophic lateral sclerosis (ALS), this suggestion was indirectly confirmed. In the current study, age-related changes in direct EEG synchrony/coherence between the brain structures were evaluated.

METHODS

In 5xFAD mice of 6-, 9-, 12-, and 18-month ages and their wild-type (WT_5xFAD) littermates, we analyzed baseline EEG coherence between the cortex, hippocampus/putamen, ventral tegmental area, and substantia nigra. Additionally, EEG coherence between the cortex and putamen was analyzed in 2- and 5-month-old FUS mice.

RESULTS

In the 5xFAD mice, suppressed levels of inter-structural coherence vs. those in WT_5xFAD littermates were observed at ages of 6, 9, and 12 months. In 18-month-old 5xFAD mice, only the hippocampus ventral tegmental area coherence was significantly reduced. In 2-month-old FUS vs. WT_FUS mice, the cortex-putamen coherence suppression, dominated in the right hemisphere, was observed. In 5-month-old mice, EEG coherence was maximal in both groups.

CONCLUSION

Neurodegenerative pathologies are accompanied by the significant attenuation of intracerebral EEG coherence. Our data are supportive for the involvement of age-related adaptive mechanisms in intracerebral disturbances produced by neurodegeneration.

Decreased coherence in the model of the dorsal visual pathway associated with Alzheimer's disease

Decreased coherence in electroencephalogram (EEG) has been reported in Alzheimer's disease (AD) experimentally, which could be considered as a typical electrophysiological characteristic in AD. This work aimed to investigate the effect of AD on coherence in the dorsal visual pathway by the technique of neurocomputation. Firstly, according to the hierarchical organization of the cerebral cortex and the information flows of the dorsal visual pathway, a more physiologically plausible neural mass model including cortical areas v1, v2, and v5 was established in the dorsal visual pathway. The three interconnected cortical areas were connected by ascending and descending projections. Next, the pathological condition of loss of long synaptic projections in AD was simulated by reducing the parameters of long synaptic projections in the model. Then, the loss of long synaptic projections on coherence among different visual cortex areas was explored by means of power spectral analysis and coherence function. The results demonstrate that the coherence between these interconnected cortical areas showed an obvious decline with the gradual decrease of long synaptic projections, i.e. decrease in descending projections from area v2 to v1 and v5 to v2 and ascending projection from area v2 to v5. Hopefully, the results of this study could provide theoretical guidance for understanding the dynamical mechanism of AD.

FSTL1-knockdown improves neural oscillation via decreasing neuronal-inflammation regulating apoptosis in Aβ1-42 induced AD model mice

Follistatin like protein 1 (FSTL1) is a famous growth regulatory protein. FSTL1 has been noticed in many diseases, including heart and lung ischemia, cerebral ischemia, glioma, schizophrenia, and Autism. The role of FSTL1 has been declared in the genetics and development of the central nervous system. Therefore, we designed this study to investigate the function and the role of FSTL1 in Alzheimer's disease. Firstly, we noticed upregulated expression level of FSTL1 among four to six-month-old 5XFAD AD mice. Accordingly, we hypothesized that FSTL1-Knockdown improved AD model mice's cognitive function and recover from Alzheimer's disease. Thus, AD model mice were made by single intracerebroventricular injections of Aβ_1-42 peptides in FSTL1^+/- and CON mice. Next, our results concluded that FSTL1-knockdown effectively improved cognitive functions. FSTL1-knockdown enhanced the pattern of neural oscillations, and synaptic plasticity in Aβ_1-42 treated FSTL1-Knockdown mice compared to Aβ_1-42 induced AD model mice. Next, FSTL1-Knockdown inhibited the activation of microglia and binding of TLR-4 with microglia. Further, inactivated microglia stopped the formation of MyD88. Thus, our data revealed that FSTL1-Knockdown is slowing down the caspase/BAX/Bcl-2/TLR-4 regulating apoptosis pathway, and the expression of inflammatory cytokines in the hippocampus of Aβ_1-42 inserted FSTL1-Knockdown mice. Overall, all these data illuminate the clinical significance role of down-regulated FSTL1. FSTL1-Knockdown reduced the amyloid-beta by affecting microglia, neural-inflammation and apoptosis in AD-like model mice. Finally, down regulation of FSTL1 improved synaptic plasticity, neural oscillations, and cognitive behaviours in the Aβ_1-42 induced AD model mice.

Functional brain changes using electroencephalography after a 24-week multidomain intervention program to prevent dementia

Quantitative electroencephalography (QEEG) has proven useful in predicting the response to various treatments, but, until now, no study has investigated changes in functional connectivity using QEEG following a lifestyle intervention program. We aimed to investigate neurophysiological changes in QEEG after a 24-week multidomain lifestyle intervention program in the SoUth Korean study to PrEvent cognitive impaiRment and protect BRAIN health through lifestyle intervention in at-risk elderly people (SUPERBRAIN). Participants without dementia and with at least one modifiable dementia risk factor, aged 60–79 years, were randomly assigned to the facility-based multidomain intervention (FMI) (n = 51), the home-based multidomain intervention (HMI) (n = 51), and the control group (n = 50). The analysis of this study included data from 44, 49, and 34 participants who underwent EEG at baseline and at the end of the study in the FMI, HMI, and control groups, respectively. The spectrum power and power ratio of EEG were calculated. Source cortical current density and functional connectivity were estimated by standardized low-resolution brain electromagnetic tomography. Participants who received the intervention showed increases in the power of the beta1 and beta3 bands and in the imaginary part of coherence of the alpha1 band compared to the control group. Decreases in the characteristic path lengths of the alpha1 band in the right supramarginal gyrus and right rostral middle frontal cortex were observed in those who received the intervention. This study showed positive biological changes, including increased functional connectivity and higher global efficiency in QEEG after a multidomain lifestyle intervention.

Clinical trial registration

[https://clinicaltrials.gov/ct2/show/NCT03980392] identifier [NCT03980392].

Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease

Alzheimer's disease dementia (ADD) is the most diffuse neurodegenerative disorder belonging to mild cognitive impairment (MCI) and dementia in old persons. This disease is provoked by an abnormal accumulation of amyloid-beta and tauopathy proteins in the brain. Very recently, the first disease-modifying drug has been licensed with reserve (i.e., Aducanumab). Therefore, there is a need to identify and use biomarkers probing the neurophysiological underpinnings of human cognitive functions to test the clinical efficacy of that drug. In this regard, event-related electroencephalographic potentials (ERPs) and oscillations (EROs) are promising candidates. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association and Global Brain Consortium reviewed the field literature on the effects of the most used symptomatic drug against ADD (i.e., Acetylcholinesterase inhibitors) on ERPs and EROs in ADD patients with MCI and dementia at the group level. The most convincing results were found in ADD patients. In those patients, Acetylcholinesterase inhibitors partially normalized ERP P300 peak latency and amplitude in oddball paradigms using visual stimuli. In these same paradigms, those drugs partially normalize ERO phase-locking at the theta band (4-7 Hz) and spectral coherence between electrode pairs at the gamma (around 40 Hz) band. These results are of great interest and may motivate multicentric, double-blind, randomized, and placebo-controlled clinical trials in MCI and ADD patients for final cross-validation.

Are there consistent abnormalities in event-related EEG oscillations in patients with Alzheimer's disease compared to other diseases belonging to dementia?

Cerebrospinal and structural-molecular neuroimaging in-vivo biomarkers are recommended for diagnostic purposes in Alzheimer's disease (AD) and other dementias; however, they do not explain the effects of AD neuropathology on neurophysiological mechanisms underpinning cognitive processes. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association reviewed the field literature and reached consensus on the event-related electroencephalographic oscillations (EROs) that show consistent abnormalities in patients with significant cognitive deficits due to Alzheimer's, Parkinson's (PD), Lewy body (LBD), and cerebrovascular diseases. Converging evidence from oddball paradigms showed that, as compared to cognitively unimpaired (CU) older adults, AD patients had lower amplitude in widespread delta (>4 Hz) and theta (4-7 Hz) phase-locked EROs as a function of disease severity. Similar effects were also observed in PD, LBD, and/or cerebrovascular cognitive impairment patients. Non-phase-locked alpha (8-12 Hz) and beta (13-30 Hz) oscillations were abnormally reduced (event-related desynchronization, ERD) in AD patients relative to CU. However, studies on patients with other dementias remain lacking. Delta and theta phase-locked EROs during oddball tasks may be useful neurophysiological biomarkers of cognitive systems at work in heuristic and intervention clinical trials performed in AD patients, but more research is needed regarding their potential role for other dementias.

Fully automated discrimination of Alzheimer's disease using resting-state electroencephalography signals

Background

The Alzheimer's disease (AD) population increases worldwide, placing a heavy burden on the economy and society. Presently, there is no cure for AD. Developing a convenient method of screening for AD and mild cognitive impairment (MCI) could enable early intervention, thus slowing down the progress of the disease and enabling better overall disease management.

Methods

In the current study, resting-state electroencephalography (EEG) data were acquired from 113 normal cognition (NC) subjects, 116 amnestic MCI patients, and 72 probable AD patients. After preprocessing by an automatic algorithm, features including spectral power, complexity, and functional connectivity were extracted, and machine-learning classifiers were built to differentiate among the 3 groups. The classification performance was evaluated from multiple perspectives, including accuracy, specificity, sensitivity, area under the curve (AUC) with 95% confidence intervals, and compared to the empirical chance level by permutation tests.

Results

The analysis of variance results (P<0.05 with false discovery rate correction) confirmed the tendency to slow brain activity, reduced complexity, and connectivity with AD progress. By combining the features, the ability of the machine-learning classifiers, especially the ensemble trees, to differentiate among the 3 groups, was significantly better than that of the empirical chance level of the permutation test. The AUC of the classifier with the best performance was 80.08% for AD vs. NC, 70.82% for AD vs. MCI, and 63.95% for MCI vs. NC.

Conclusions

The current study presented a fully automatic procedure that could significantly distinguish NC, MCI, and AD subjects via resting-state EEG signals. The study was based on a large data set with evidence-based medical diagnosis and provided further evidence that resting-state EEG data could assist in the discrimination of AD patients.

Decreased Right Prefrontal Synchronization Strength and Asymmetry During Joint Attention in the Left-Behind Children: A Functional Near-Infrared Spectroscopy Study

Although there are millions of left-behind children in China, the researches on brain structure and functions in left-behind children are not sufficient at the brain imaging level. This study aimed to explore whether there is decreased prefrontal synchronization during joint attention in left-behind children. Sixty children (65.12 ± 6.54 months, 29 males) with 34 left-behind children were recruited. The functional near-infrared spectroscopy (fNIRS) imaging data from the prefrontal cortex during joint attention, as well as behavioral measures (associated with family income, intelligence, language, and social-emotional abilities), were collected. Results verified that brain imaging data and behavioral measures are correlative and support that left-behind children have deficits in social-emotional abilities. More importantly, left-behind children showed decreased synchronization strength and asymmetry in the right middle frontal gyrus during joint attention. The findings suggest that decreased right prefrontal synchronization strength and asymmetry during joint attention might be vulnerability factors in the development of left-behind children.

Analysis of Endogenous Spectral Power of EEG Alpha-Range Biopotentials during Mnestic Activity under Conditions of Rhythmically Organized Optical Stimulation

We studied the effect of optical stimulation (10 Hz) on the effectiveness of mnestic activity in the n-back task in healthy subjects (n=32). EEG was recorded at all stages of the examination. The absolute values of the spectral power of the 10 Hz frequency (μV2) of the alpha range were calculated. According to the results of the test without optical stimulation, the examinees were divided into groups with high (group 1) and low (group 2) task performance. In the initial state, the spectral power of 10 Hz was significantly higher in group 1 subjects. Under conditions of screen flickering, the results became poorer in group 1 and better in group 2 in comparison with the results under normal conditions. These changes were accompanied by an increase in the spectral power of 10 Hz only in group 2 subjects. These findings can provide the basis for the development of practical recommendations for improving the mnestic functions in patients with consideration for the individual characteristics of their initial EEG.

EEG Resting-State and Event-Related Potentials as Markers of Learning Success in Older Adults Following Second Language Training: A Pilot Study

OBJECTIVES

In this pilot study, we evaluated the use of electrophysiological measures at rest as paradigm-independent predictors of second language (L2) development for the first time in older adult learners. We then assessed EEG correlates of the learning outcome in a language-switching paradigm after the training, which to date has only been done in younger adults and at intermediate to advanced L2 proficiency.

METHODS

Ten (Swiss) German-speaking adults between 65-74 years of age participated in an intensive 3-week English training for beginners. A resting-state EEG was recorded before the training to predict the ensuing L2 development (Experiment 1). A language-switching ERP experiment was conducted after the training to assess the learning outcome (Experiment 2).

RESULTS

All participants improved their L2 skills but differed noticeably in their individual development. Experiment 1 showed that beta1 oscillations at rest (13-14.5 Hz) predicted these individual differences. We interpret resting-state beta1 oscillations as correlates of attentional capacities and semantic working memory that facilitate the extraction and processing of novel forms and meanings from the L2 input.In Experiment 2, we found that language switching from the L2 into the native language (L1) elicited an N400 component, which was reduced in the more advanced learners. Thus, for learners beginning the acquisition of an L2 in third age, language switching appears to become less effortful with increasing proficiency, suggesting that the lexicons of the L1 and L2 become more closely linked.

CONCLUSIONS

In sum, our findings extend the available evidence of neurological processes in L2 learning from younger to older adults, suggesting that electrophysiological mechanisms are similar across the lifespan.

Functional (un-)Coupling: Impairment, Compensation, and Future Progression in Alzheimer's Disease

Background: Functional (un-)coupling (task-related change of functional connectivity) between different sites of the brain is a mechanism of general importance for cognitive processes. In Alzheimer's disease (AD), prior research identified diminished cortical connectivity as a hallmark of the disease. However, little is known about the relation between the amount of functional (un-)coupling and cognitive performance and decline in AD. Method: Cognitive performance (based on CERAD-Plus scores) and electroencephalogram (EEG)-based functional (un-)coupling measures (connectivity changes from rest to a Face-Name-Encoding task) were assessed in 135 AD patients (age: M = 73.8 years; SD = 9.0). Of these, 68 patients (M = 73.9 years; SD = 8.9) participated in a follow-up assessment of their cognitive performance 1.5 years later. Results: The amounts of functional (un-)coupling in left anterior-posterior and homotopic interhemispheric connections in beta1-band were related to cognitive performance at baseline (β = .340; p < .001; β = .274; P = .001, respectively). For both markers, a higher amount of functional coupling was associated with better cognitive performance. Both markers also were significant predictors for cognitive decline. However, while patients with greater functional coupling in left anterior-posterior connections declined less in cognitive performance (β = .329; P = .035) those with greater functional coupling in interhemispheric connections declined more (β = -.402; P = .010). Conclusion: These findings suggest an important role of functional coupling mechanisms in left anterior-posterior and interhemispheric connections in AD. Especially the complex relationship with cognitive decline in AD patients might be an interesting aspect for future studies.

EEG Alpha and Beta Band Functional Connectivity and Network Structure Mark Hub Overload in Mild Cognitive Impairment During Memory Maintenance

Background: While decreased alpha and beta-band functional connectivity (FC) and changes in network topology have been reported in Alzheimer's disease, it is not yet entirely known whether these differences can mark cognitive decline in the early stages of the disease. Our study aimed to analyze electroencephalography (EEG) FC and network differences in the alpha and beta frequency band during visuospatial memory maintenance between Mild Cognitive Impairment (MCI) patients and healthy elderly with subjective memory complaints. Methods: Functional connectivity and network structure of 17 MCI patients and 20 control participants were studied with 128-channel EEG during a visuospatial memory task with varying memory load. FC between EEG channels was measured by amplitude envelope correlation with leakage correction (AEC-c), while network analysis was performed by applying the Minimum Spanning Tree (MST) approach, which reconstructs the critical backbone of the original network. Results: Memory load (increasing number of to-be-learned items) enhanced the mean AEC-c in the control group in both frequency bands. In contrast to that, after an initial increase, the MCI group showed significantly (p < 0.05) diminished FC in the alpha band in the highest memory load condition, while in the beta band this modulation was absent. Moreover, mean alpha and beta AEC-c correlated significantly with the size of medial temporal lobe structures in the entire sample. The network analysis revealed increased maximum degree, betweenness centrality, and degree divergence, and decreased diameter and eccentricity in the MCI group compared to the control group in both frequency bands independently of the memory load. This suggests a rerouted network in the MCI group with a more centralized topology and a more unequal traffic load distribution. Conclusion: Alpha- and beta-band FC measured by AEC-c correlates with cognitive load-related modulation, with subtle medial temporal lobe atrophy, and with the disruption of hippocampal fiber integrity in the earliest stages of cognitive decline. The more integrated network topology of the MCI group is in line with the "hub overload and failure" framework and might be part of a compensatory mechanism or a consequence of neural disinhibition.

Clustering of Brain Tumor Based on Analysis of MRI Images Using Robust Principal Component Analysis (ROBPCA) Algorithm

Automated detection of brain tumor location is essential for both medical and analytical uses. In this paper, we clustered brain MRI images to detect tumor location. To obtain perfect results, we presented an unsupervised robust PCA algorithm to clustered images. The proposed method clusters brain MR image pixels to four leverages. The algorithm is implemented for five brain diseases such as glioma, Huntington, meningioma, Pick, and Alzheimer's. We used ten images of each disease to validate the optimal identification rate. According to the results obtained, 2% of the data in the bad leverage part of the image were determined, which acceptably discerned the tumor. Results show that this method has the potential to detect tumor location for brain disease with high sensitivity. Moreover, results show that the method for the Glioma images has approximately better results than others. However, according to the ROC curve for all selected diseases, the present method can find lesion location.

EEG Coherence Metrics for Vigilance: Sensitivity to Workload, Time-on-Task, and Individual Differences

The vigilance decrement in performance is a significant operational issue in various applied settings. Psychophysiological methods for diagnostic monitoring of vigilance have focused on power spectral density measures from the electroencephalogram (EEG). This article addresses the diagnosticity of an alternative set of EEG measures, coherence between different electrode sites. Coherence metrics may index the functional connectivity between brain regions that supports sustained attention. Coherence was calculated for seven pre-defined brain networks. Workload and time-on-task factors primarily influenced alpha and theta coherence in anterior, central, and inter-hemispheric networks. Individual differences in coherence in inter-hemispheric, left intro-hemispheric and posterior networks correlated with performance. These findings demonstrate the potential applied utility of coherence metrics, although several methodological limitations and challenges must be overcome.

Psycho-Electrophysiological Benefits of Forest Therapies Focused on Qigong and Walking with Elderly Individuals

We developed two distinct forest therapy programs (FTPs) and compared their effects on dementia prevention and related health problems for older adults. One was focused on Qigong practice in the forest (QP) and the other involved active walking in the forest (WP). Both FTPs consisted of twelve 2-h sessions over six weeks and were conducted in an urban forest. We obtained data from 25, 18, and 26 participants aged 65 years or above for the QP, WP, and control groups, respectively. Neuropsychological scores via cognition (MoCA), geriatric depression (GDS) and quality of life (EQ-5D), and electrophysiological variables (electroencephalography, bioimpedance, and heart rate variability) were measured. We analyzed the intervention effects with a generalized linear model. Compared to the control group, the WP group showed benefits in terms of neurocognition (increases in the MoCA score, and alpha and beta band power values in the electroencephalogram), sympathetic nervous activity, and bioimpedance in the lower body. On the other hand, the QP group showed alleviated depression and an increased bioimpedance phase angle in the upper body. In conclusion, both active walking and Qigong in the forest were shown to have distinctive neuropsychological and electrophysiological benefits, and both had beneficial effects in terms of preventing dementia and relieving related health problems for elderly individuals.

Distinct Functional Connectivity Patterns Are Associated With Social and Cognitive Lifestyle Factors: Pathways to Cognitive Reserve

The importance of diverse lifestyle factors in sustaining cognition during aging and delaying the onset of decline in Alzheimer's disease and related dementias cannot be overstated. We explored the influence of cognitive, social, and physical lifestyle factors on resting-state lagged linear connectivity (LLC) in high-density electroencephalography (EEG) in adults, ages 35-75 years. Diverse lifestyle factors build cognitive reserve (CR), protecting cognition in the presence of physical brain decline. Differences in LLC were examined between high- and low-CR groups formed using cognitive, social, and exercise lifestyle factors. LLC is a measure of lagged coherence that excludes zero phase contributions and limits the effects of volume conduction on connectivity estimates. Significant differences in LLC were identified for cognitive and social factors, but not exercise. Participants high in social CR possessed greater local and long-range connectivity in theta and low alpha for eyes-open and eyes-closed recording conditions. In contrast, participants high in cognitive CR exhibited greater eyes-closed long-range connectivity between the occipital lobe and other cortical regions in low alpha. Greater eyes-closed local LLC in delta was also present in men high in cognitive CR. Cognitive factor scores correlated with sustained attention, whereas social factors scores correlated with spatial working memory. Gender was a significant covariate in our analyses, with women displaying higher local and long-range LLC in low beta. Our findings support distinct relationships between CR and LLC, as well as CR and cognitive function for cognitive and social subcomponents. These patterns reflect the importance of diverse lifestyle factors in building CR.

Traditional Korean Medicine-Based Forest Therapy Programs Providing Electrophysiological Benefits for Elderly Individuals

We aimed to develop forest therapy programs (FTPs) to prevent dementia and related health problems in the elderly population, with the assumption that health benefits are FTP-type specific and depend on the participant's psychophysiological traits. For this purpose, we developed two distinct FTPs, namely, a guided-breathing meditation program (BP) and a walking program (WP); we adopted the approach of Sasang constitutional (SC) medicine, which categorizes individuals into one of three SC types (SC1, SC2, or SC3) for medical care. The FTPs ran 11 sessions over 11 weeks. We recruited 29/31/28 participants who were 65 years of age or older for the BP/WP/control groups, respectively; obtained electrophysiological measurements via electroencephalogram (EEG), heart rate variability (HRV), and bioimpedance; and analyzed the intervention effects with analysis of covariance. Compared with the control, the BP and WP resulted in benefits for neural activity and parasympathetic nervous activity (PNA), respectively, and both FTPs yielded distinct beneficial effects on bioimpedance. Constitution-specific effects were also present. The SC1- and SC2-type participants gained positive effects in neural activity from the BP and WP, respectively. The SC3-type participants showed improvements in PNA from the WP. In conclusion, for older individuals, both programs conferred health benefits that would help prevent dementia, and the benefits were program-specific and constitution-specific.

Self-initiated learning reveals memory performance and electrophysiological differences between younger, older and older adults with relative memory impairment

Older adults display difficulties in encoding and retrieval of information, resulting in poorer memory. This may be due to an inability of older adults to engage elaborative encoding strategies during learning. This study examined behavioural and electrophysiological effects of explicit cues to self-initiate learning during encoding and subsequent recognition of words in younger adults (YA), older control adults (OA) and older adults with relative memory impairment (OD). The task was a variation of the old/new paradigm, some study items were preceded by a cue to learn the word (L) while others by a do not learn cue (X). Behaviourally, YA outperformed OA and OD on the recognition task, with no significant difference between OA and OD. Event-related potentials at encoding revealed enhanced early visual processing (70-140 ms) for L- versus X-words in young and old. Only YA exhibited a greater late posterior positivity (LPP; 200-500 ms) for all words during encoding perhaps reflecting superior encoding strategy. During recognition, only YA differentiated L- versus X-words with enhanced frontal P200 (150-250 ms) suggesting impaired early word selection for retrieval in older groups; however, OD had enhanced P200 activity compared to OA during L-word retrieval. The LPP (250-500 ms) was reduced in amplitude for L-words compared to both X- and new words. However, YA showed greater LPP amplitude for all words compared to OA. For older groups, we observed reduced left parietal hemispheric asymmetry apparent in YA during encoding and recognition, especially for OD. Findings are interpreted in the light of models of compensation and dedifferentiation associated with age-related changes in memory function.

Changes in Theta but not Alpha Modulation Are Associated with Impairment in Working Memory in Alzheimer's Disease and Mild Cognitive Impairment

While several studies have found that neural oscillations play a key role in the functioning of working memory, the nature of aberrant oscillatory activity underlying working memory impairments in Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains largely unexplored. These individuals often display structural alterations in brain regions and pathways involved in working memory processes and therefore may also display altered oscillatory activity during memory activation. Electroencephalographic (EEG) activity was recorded during the N-back working memory task in three groups: AD (n = 29), MCI (n = 100), and healthy controls (HCs; n = 40). Theta (4-7 Hz) and alpha (7.5-12 Hz) modulation was measured in response to the stimulus presentation during correct and incorrect responses. This modulation represents the change in EEG activity associated with the stimulus onset and was measured as a ratio of post stimulus power to pre stimulus power. We also assessed the relationship between change in oscillatory power and working memory performance. Compared to HCs, the AD group demonstrated the lowest working memory accuracy and a smaller theta ratio for correct responses on the 2-back condition; the MCI group demonstrated a smaller theta ratio for correct responses on the 3-back condition. Finally, we observed that the theta ratio, but not the alpha ratio, was a significant predictor of working memory performance in the three groups for all conditions. Taken together, these behavioral and electrophysiological results suggest that in addition to impairments in working memory performance, modulation of theta, but not alpha power, may be impaired in MCI and AD.

Neuroimaging markers of global cognition in early Alzheimer's disease: A magnetic resonance imaging-electroencephalography study

INTRODUCTION

Magnetic resonance imaging (MRI) and electroencephalography (EEG) are a promising means to an objectified assessment of cognitive impairment in Alzheimer's disease (AD). Individually, however, these modalities tend to lack precision in both AD diagnosis and AD staging. A joint MRI-EEG approach that combines structural with functional information has the potential to overcome these limitations.

MATERIALS AND METHODS

This cross-sectional study systematically investigated the link between MRI and EEG markers and the global cognitive status in early AD. We hypothesized that the joint modalities would identify cognitive deficits with higher accuracy than the individual modalities. In a cohort of 111 AD patients, we combined MRI measures of cortical thickness and regional brain volume with EEG measures of rhythmic activity, information processing and functional coupling in a generalized multiple regression model. Machine learning classification was used to evaluate the markers' utility in accurately separating the subjects according to their cognitive score.

RESULTS

We found that joint measures of temporal volume, cortical thickness, and EEG slowing were well associated with the cognitive status and explained 38.2% of ifs variation. The inclusion of the covariates age, sex, and education considerably improved the model. The joint markers separated the subjects with an accuracy of 84.7%, which was considerably higher than by using individual modalities.

CONCLUSIONS

These results suggest that including joint MRI-EEG markers may be beneficial in the diagnostic workup, thus allowing for adequate treatment. Further studies in larger populations, with a longitudinal design and validated against functional-metabolic imaging are warranted to confirm the results.

Coherence and phase synchrony analyses of EEG signals in Mild Cognitive Impairment (MCI): A study of functional brain connectivity

This paper presents an EEG study for coherence and phase synchrony in mild cognitive impairment (MCI) subjects. MCI is characterized by cognitive decline, which is an early stage of Alzheimer’s disease (AD). AD is a neurodegenerative disorder with symptoms such as memory loss and cognitive impairment. EEG coherence is a statistical measure of correlation between signals from electrodes spatially separated on the scalp. The magnitude of phase synchrony is expressed in the phase locking value (PLV), a statistical measure of neuronal connectivity in the human brain. Brain signals were recorded using an Emotiv Epoc 14-channel wireless EEG at a sampling frequency of 128 Hz. In this study, we used 22 elderly subjects consisted of 10 MCI subjects and 12 healthy subjects as control group. The coherence between each electrode pair was measured for all frequency bands (delta, theta, alpha and beta). In the MCI subjects, the value of coherence and phase synchrony was generally lower than in the healthy subjects especially in the beta frequency. A decline of intrahemisphere coherence in the MCI subjects occurred in the left temporo-parietal-occipital region. The pattern of decline in MCI coherence is associated with decreased cholinergic connectivity along the path that connects the temporal, occipital, and parietal areas of the brain to the frontal area of the brain. EEG coherence and phase synchrony are able to distinguish persons who suffer AD in the early stages from healthy elderly subjects.

Analysis of long range dependence in the EEG signals of Alzheimer patients

Alzheimer's disease (AD), a cognitive disability is analysed using a long range dependence parameter, hurst exponent (HE), calculated based on the time domain analysis of the measured electrical activity of brain. The electroencephalogram (EEG) signals of controls and mild cognitive impairment (MCI)-AD patients are evaluated under normal resting and mental arithmetic conditions. Simultaneous low pass filtering and total variation denoising algorithm is employed for preprocessing. Larger values of HE observed in the right hemisphere of the brain for AD patients indicated a decrease in irregularity of the EEG signal under cognitive task conditions. Correlations between HE and the neuropsychological indices are analysed using bivariate correlation analysis. The observed reduction in the values of Auto mutual information and cross mutual information in the local antero-frontal and distant regions in the brain hemisphere indicates the loss of information transmission in MCI-AD patients.

Analysis of long range dependence in the EEG signals of Alzheimer patients

Alzheimer's disease (AD), a cognitive disability is analysed using a long range dependence parameter, hurst exponent (HE), calculated based on the time domain analysis of the measured electrical activity of brain. The electroencephalogram (EEG) signals of controls and mild cognitive impairment (MCI)-AD patients are evaluated under normal resting and mental arithmetic conditions. Simultaneous low pass filtering and total variation denoising algorithm is employed for preprocessing. Larger values of HE observed in the right hemisphere of the brain for AD patients indicated a decrease in irregularity of the EEG signal under cognitive task conditions. Correlations between HE and the neuropsychological indices are analysed using bivariate correlation analysis. The observed reduction in the values of Auto mutual information and cross mutual information in the local antero-frontal and distant regions in the brain hemisphere indicates the loss of information transmission in MCI-AD patients.

Electrophysiological impact of multiple concussions in asymptomatic athletes: A re-analysis based on alpha activity during a visual-spatial attention task

Most EEG studies used event-related potentials to assess long-term and cumulative effects of sport-related concussions on brain activity. Time-frequency methods provide another approach that allows the detection of subtle shifts in types and patterns of brain oscillations. We sought to discover whether event-related alpha activity would be significantly affected in asymptomatic multi-concussed athletes. We measured the amplitude of alpha activity (8-12Hz) from the EEG recorded during a visual-spatial attention task to compare event-related alpha perturbations in 13 multi-concussed athletes and 14 age-equivalent, non-concussed teammates. Relative to non-concussed athletes, multi-concussed athletes showed significantly less event-related perturbations time-locked to stimulus presentation. Alpha activity alterations were closely related to the number of concussions sustained. Event-related alpha activity differed in asymptomatic multi-concussed athletes when compared to controls. Our study suggests that low-level neurophysiological underpinnings of the deployment of visual-spatial attention are affected in multi-concussed athletes even though their last concussion occurred on average 30 months prior to testing.

Enhanced Gamma Activity and Cross-Frequency Interaction of Resting-State Electroencephalographic Oscillations in Patients with Alzheimer's Disease

Cognitive impairment, functional decline and behavioral symptoms that characterize Alzheimer’s disease (AD) are associated with perturbations of the neuronal network. The typical electroencephalographic (EEG) features in AD patients are increased delta or theta rhythm and decreased alpha or beta rhythm activities. However, considering the role of cross-frequency couplings in cognition, the alternation of cross-frequency couplings in AD patients is still obscure. This study aims to explore the interaction dynamics between different EEG oscillations in AD patients. We recorded the resting eye-closed EEG signals in 8 AD patients and 12 healthy volunteers. By analyzing the wavelet power spectrum and bicoherence of EEG, we found enhanced gamma rhythm power in AD patients in addition to the increased delta and decreased alpha power. Furthermore, an enhancement of the cross-frequency coupling strength between the beta/gamma and low-frequency bands was observed in AD patients compared to healthy controls (HCs). We propose that the pathological increase of ongoing gamma-band power might result from the disruption of the GABAergic interneuron network in AD patients. Furthermore, the cross-frequency overcouplings, which reflect the enhanced synchronization, might indicate the attenuated complexity of the neuronal network, and AD patients have to use more neural resources to maintain the resting brain state. Overall, our findings provide new evidence of the disturbance of the brain oscillation network in AD and further deepen our understanding of the central mechanisms of AD.

Increased long distance event-related gamma band connectivity in Alzheimer's disease

BACKGROUND

Brain oscillatory responses can be used for non-invasive analyses of cortico-cortical connectivity, local neuronal synchronization, and coherence of oscillations in many neuropsychiatric conditions including Alzheimer's disease (AD). In the present paper, we examine sensory-evoked and event-related gamma coherences elicited by visual stimuli in three sub-gamma bands in two sub-groups of patients with AD (i.e., acetylcholinesterase-inhibitor treated and untreated) and healthy controls.

METHODS

We studied a total of 39 patients with probable mild AD (according to NINCDS-ADRDA criteria) who had been sub-divided into untreated (n = 21) and treated (n = 18) (patients either on cholinergic monotherapy or combined therapy with memantine) AD groups, and 21 age-, gender-, and education-matched healthy elderly controls. A simple flash visual paradigm was applied for the acquisition of sensory-evoked coherences. Event-related coherences were elicited using a classical visual oddball paradigm. Both sensory-evoked and event-related gamma coherences were calculated for long-distance intrahemispheric pairs for three frequency ranges: 25-30 Hz, 30-35 Hz, and 40-48 Hz in post-stimulus 0-800 ms duration. The long-distance intrahemispheric pairs from both sides were fronto-parietal, fronto-temporal, fronto-temporoparietal, fronto-occipital, centro-occipital and parieto-occipital.

RESULTS

The sensory-evoked or event-related gamma coherences revealed that both treated and untreated AD patients had significantly increased values compared to healthy controls in all three sub-gamma bands. Moreover, the treated AD patients demonstrated significantly higher fronto-parietal gamma coherences during both sensory stimulation and oddball paradigm and lower occipito-parietal coherences during oddball paradigm in comparison to untreated AD patients.

CONCLUSION

The present study demonstrated that an increase of gamma coherences was present in response to both visual sensory and cognitive stimulation in AD patients in all gamma sub-bands. Therefore, gamma oscillatory activity seems to be fundamental in brain functions at both the sensory and cognitive levels. The increase of gamma coherence values was not due to cholinergic treatment to any significant extent, as both treated and untreated AD patients had increased gamma coherence values compared to healthy controls. The use of coherence values reflecting brain connectivity holds potential for neuroimaging of AD and understanding brain dynamics related to the effects of medication.

Speech rhythm alterations in Spanish-speaking individuals with Alzheimer's disease

Rhythm is the speech property related to the temporal organization of sounds. Considerable evidence is now available for suggesting that dementia of Alzheimer's type is associated with impairments in speech rhythm. The aim of this study is to assess the use of an automatic computerized system for measuring speech rhythm characteristics in an oral reading task performed by 45 patients with Alzheimer's disease (AD) compared with those same characteristics among 82 healthy older adults without a diagnosis of dementia, and matched by age, sex and cultural background. Ranges of rhythmic-metric and clinical measurements were applied. The results show rhythmic differences between the groups, with higher variability of syllabic intervals in AD patients. Signal processing algorithms applied to oral reading recordings prove to be capable of differentiating between AD patients and older adults without dementia with an accuracy of 87% (specificity 81.7%, sensitivity 82.2%), based on the standard deviation of the duration of syllabic intervals. Experimental results show that the syllabic variability measurements extracted from the speech signal can be used to distinguish between older adults without a diagnosis of dementia and those with AD, and may be useful as a tool for the objective study and quantification of speech deficits in AD.

Functional Brain Networks: Does the Choice of Dependency Estimator and Binarization Method Matter?

The human brain can be modelled as a complex networked structure with brain regions as individual nodes and their anatomical/functional links as edges. Functional brain networks are constructed by first extracting weighted connectivity matrices, and then binarizing them to minimize the noise level. Different methods have been used to estimate the dependency values between the nodes and to obtain a binary network from a weighted connectivity matrix. In this work we study topological properties of EEG-based functional networks in Alzheimer’s Disease (AD). To estimate the connectivity strength between two time series, we use Pearson correlation, coherence, phase order parameter and synchronization likelihood. In order to binarize the weighted connectivity matrices, we use Minimum Spanning Tree (MST), Minimum Connected Component (MCC), uniform threshold and density-preserving methods. We find that the detected AD-related abnormalities highly depend on the methods used for dependency estimation and binarization. Topological properties of networks constructed using coherence method and MCC binarization show more significant differences between AD and healthy subjects than the other methods. These results might explain contradictory results reported in the literature for network properties specific to AD symptoms. The analysis method should be seriously taken into account in the interpretation of network-based analysis of brain signals.

Electroencephalogram associations to cognitive performance in clinically active nurses

Cognitive impairment is traditionally identified via cognitive screening tools that have limited ability in detecting early or transitional stages of impairment. The dynamic nature of physiological variables such as the electroencephalogram (EEG) may provide alternate means for detecting these transitions. However, previous research examining EEG and cognitive performance is largely confined to samples with diagnosed cognitive impairments, and research examining non-impaired, and occupation specific samples, is limited. The present study aimed to investigate the associations between frontal pole and central EEG and cognitive performance in a sample of male and female nurses, and to determine the significance of these associations. Fifty seven nurses participated in the study, in which two lead bipolar EEG was recorded at positions Fp1 (frontal polar), Fp2, C3 (central) and C4 during a baseline and an active phase involving the common neuropsychological Stroop test. Participants' cognitive performance was assessed using the mini-mental state exam (MMSE) and Cognistat screening tools. Significant correlations between EEG beta activity and the outcome of MMSE and Cognistat were revealed, where an increased beta activity was associated to an increased global cognitive performance. Additionally, domain specific cognitive performance was also significantly associated to various EEG variables. The study identified potential EEG biomarkers for global and domain specific cognitive performance, and provides initial groundwork for the development of future EEG based biomarkers for detection of cognitive pathologies.

Transcranial Direct Current Stimulation Modulates Cortical Neuronal Activity in Alzheimer's Disease

Quantitative electroencephalography (qEEG) showed that Alzheimer's disease (AD) is characterized by increased theta power, decreased alpha and beta power, and decreased coherence in the alpha and theta band in posterior regions. These abnormalities are thought to be associated with functional disconnections among cortical areas, death of cortical neurons, axonal pathology, and cholinergic deficits. Since transcranial Direct Current Stimulation (tDCS) over the temporo-parietal area is thought to have beneficial effects in patients with AD, in this study we aimed to investigate whether tDCS benefits are related to tDCS-induced changes in cortical activity, as represented by qEEG. A weak anodal current (1.5 mA, 15 min) was delivered bilaterally over the temporal-parietal lobe to seven subjects with probable AD (Mini-Mental State Examination, MMSE score >20). EEG (21 electrodes, 10–20 international system) was recorded for 5 min with eyes closed before (baseline, t0) and 30 min after anodal and cathodal tDCS ended (t1). At the same time points, patients performed a Word Recognition Task (WRT) to assess working memory functions. The spectral power and the inter- and intra-hemispheric EEG coherence in different frequency bands (e.g., low frequencies, including delta and theta; high frequencies, including alpha and beta) were calculated for each subject at t0 and t1. tDCS-induced changes in EEG neurophysiological markers were correlated with the performance of patients at the WRT. At baseline, qEEG features in AD patients confirmed that the decreased high frequency power was correlated with lower MMSE. After anodal tDCS, we observed an increase in the high-frequency power in the temporo-parietal area and an increase in the temporo-parieto-occipital coherence that correlated with the improvement at the WRT. In addition, cathodal tDCS produced a non-specific effect of decreased theta power all over the scalp that was not correlated with the clinical observation at the WRT. Our findings disclosed that tDCS induces significant modulations in the cortical EEG activity in AD patients. The abnormal pattern of EEG activity observed in AD during memory processing is partially reversed by applying anodal tDCS, suggesting that anodal tDCS benefits in AD patients during working memory tasks are supported by the modulation of cortical activity.

Quantifying synchrony patterns in the EEG of Alzheimer's patients with linear and non-linear connectivity markers

We analyzed the relation of several synchrony markers in the electroencephalogram (EEG) and Alzheimer's disease (AD) severity as measured by Mini-Mental State Examination (MMSE) scores. The study sample consisted of 79 subjects diagnosed with probable AD. All subjects were participants in the PRODEM-Austria study. Following a homogeneous protocol, the EEG was recorded both in resting state and during a cognitive task. We employed quadratic least squares regression to describe the relation between MMSE and the EEG markers. Factor analysis was used for estimating a potentially lower number of unobserved synchrony factors. These common factors were then related to MMSE scores as well. Most markers displayed an initial increase of EEG synchrony with MMSE scores from 26 to 21 or 20, and a decrease below. This effect was most prominent during the cognitive task and may be owed to cerebral compensatory mechanisms. Factor analysis provided interesting insights in the synchrony structures and the first common factors were related to MMSE scores with coefficients of determination up to 0.433. We conclude that several of the proposed EEG markers are related to AD severity for the overall sample with a wide dispersion for individual subjects. Part of these fluctuations may be owed to fluctuations and day-to-day variability associated with MMSE measurements. Our study provides a systematic analysis of EEG synchrony based on a large and homogeneous sample. The results indicate that the individual markers capture different aspects of EEG synchrony and may reflect cerebral compensatory mechanisms in the early stages of AD.

Using static and dynamic canonical correlation coefficients as quantitative EEG markers for Alzheimer's disease severity

We analyzed the relation between Alzheimer's disease (AD) severity as measured by Mini-Mental State Examination (MMSE) scores and quantitative electroencephalographic (qEEG) markers that were derived from canonical correlation analysis. This allowed an investigation of EEG synchrony between groups of EEG channels. In this study, we applied the data from 79 participants in the multi-centric cohort study PRODEM-Austria with probable AD. Following a homogeneous protocol, the EEG was recorded both in resting state and during a cognitive task. A quadratic regression model was used to describe the relation between MMSE and the qEEG synchrony markers. This relation was most significant in the δ and θ frequency bands in resting state, and between left-hemispheric central, temporal and parietal channel groups during the cognitive task. Here, the MMSE explained up to 40% of the qEEG marker's variation. QEEG markers showed an ambiguous trend, i.e. an increase of EEG synchrony in the initial stage of AD (MMSE>20) and a decrease in later stages. This effect could be caused by compensatory brain mechanisms. We conclude that the proposed qEEG markers are closely related to AD severity. Despite the ambiguous trend and the resulting diagnostic ambiguity, the qEEG markers could provide aid in the diagnostics of early-stage AD.

Mild Cognitive Impairment: Structural, Metabolical, and Neurophysiological Evidence of a Novel EEG Biomarker

BACKGROUND

Recent studies demonstrate that the alpha3/alpha2 power ratio correlates with cortical atrophy, regional hypoperfusion, and memory impairment in subjects with mild cognitive impairment (MCI).

METHODS

Evidences were reviewed in subjects with MCI, who underwent EEG recording, magnetic resonance imaging (MRI) scans, and memory evaluation. Alpha3/alpha2 power ratio (alpha2 8.9-10.9 Hz range; alpha3 10.9-12.9 Hz range), cortical thickness, linear EEG coherence, and memory impairment have been evaluated in a large group of 74 patients. A subset of 27 subjects within the same group also underwent single photon emission computed tomography (SPECT) evaluation.

RESULTS

In MCI subjects with higher EEG upper/low alpha power ratio, a greater temporo-parietal and hippocampal atrophy was found as well as a decrease in regional blood perfusion and memory impairment. In this group, an increase of theta oscillations is associated with a greater interhemispheric coupling between temporal areas.

CONCLUSION

The increase of alpha3/alpha2 power ratio is a promising novel biomarker in identifying MCI subjects at risk for Alzheimer's disease.

Understanding early dementia: EEG, MRI, SPECT and memory evaluation

BACKGROUND

An increase in the EEG upper/low α power ratio has been associated with mild cognitive impairment (MCI) due to Alzheimer's disease (AD) and to the atrophy of temporoparietal brain areas. Subjects with a higher α3/α2 frequency power ratio showed lower brain perfusion than in the low α3/α2 group. The two groups show significantly different hippocampal volumes and correlation with θ frequency activity.

METHODS

Seventy-four adult subjects with MCI underwent clinical and neuropsychological evaluation, electroencephalogram (EEG) recording, and high resolution 3D magnetic resonance imaging (MRI). Twenty-seven of them underwent EEG recording and perfusion single-photon emission computed tomography (SPECT) evaluation. The α3/α2 power ratio and cortical thickness were computed for each subject. The difference in cortical thickness between the groups was estimated.

RESULTS

In the higher upper/low α group, memory impairment was more pronounced in both the MRI group and the SPECT MCI groups. An increase in the production of θ oscillations was associated with greater interhemisperic coupling between temporal areas. It also correlated with greater cortical atrophy and lower perfusional rate in the temporoparietal cortex.

CONCLUSION

High EEG upper/low α power ratio was associated with cortical thinning and lower perfusion in temporoparietal areas. Moreover, both atrophy and lower perfusion rate significantly correlated with memory impairment in MCI subjects. Therefore, the increase in the EEG upper/low α frequency power ratio could be useful in identifying individuals at risk for progression to AD dementia in a clinical context.

A novel method of early diagnosis of Alzheimer's disease based on EEG signals

Studies have reported that electroencephalogram signals in Alzheimer's disease patients usually have less synchronization than those of healthy subjects. Changes in electroencephalogram signals start at early stage but, clinically, these changes are not easily detected. To detect this perturbation, three neural synchrony measurement techniques: phase synchrony, magnitude squared coherence, and cross correlation are applied to three different databases of mild Alzheimer's disease patients and healthy subjects. We have compared the right and left temporal lobes of the brain with the rest of the brain areas (frontal, central, and occipital) as temporal regions are relatively the first ones to be affected by Alzheimer's disease. Moreover, electroencephalogram signals are further classified into five different frequency bands (delta, theta, alpha beta, and gamma) because each frequency band has its own physiological significance in terms of signal evaluation. A new approach using principal component analysis before applying neural synchrony measurement techniques has been presented and compared with Average technique. The simulation results indicated that applying principal component analysis before synchrony measurement techniques shows significantly better results as compared to the lateral one. At the end, all the aforementioned techniques are assessed by a statistical test (Mann-Whitney U test) to compare the results.

Power spectral density and coherence analysis of Alzheimer's EEG

In this paper, we investigate the abnormalities of electroencephalograph (EEG) signals in the Alzheimer's disease (AD) by analyzing 16-scalp electrodes EEG signals and make a comparison with the normal controls. The power spectral density (PSD) which represents the power distribution of EEG series in the frequency domain is used to evaluate the abnormalities of AD brain. Spectrum analysis based on autoregressive Burg method shows that the relative PSD of AD group is increased in the theta frequency band while significantly reduced in the alpha2 frequency bands, particularly in parietal, temporal, and occipital areas. Furthermore, the coherence of two EEG series among different electrodes is analyzed in the alpha2 frequency band. It is demonstrated that the pair-wise coherence between different brain areas in AD group are remarkably decreased. Interestingly, this decrease of pair-wise electrodes is much more significant in inter-hemispheric areas than that in intra-hemispheric areas. Moreover, the linear cortico-cortical functional connectivity can be extracted based on coherence matrix, from which it is shown that the functional connections are obviously decreased, the same variation trend as relative PSD. In addition, we combine both features of the relative PSD and the normalized degree of functional network to discriminate AD patients from the normal controls by applying a support vector machine model in the alpha2 frequency band. It is indicated that the two groups can be clearly classified by the combined feature. Importantly, the accuracy of the classification is higher than that of any one feature. The obtained results show that analysis of PSD and coherence-based functional network can be taken as a potential comprehensive measure to distinguish AD patients from the normal, which may benefit our understanding of the disease.

The Road Ahead to Cure Alzheimer's Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations

Alzheimer's disease (AD) is a slowly progressing non-linear dynamic brain disease in which pathophysiological abnormalities, detectable in vivo by biological markers, precede overt clinical symptoms by many years to decades. Use of these biomarkers for the detection of early and preclinical AD has become of central importance following publication of two international expert working group's revised criteria for the diagnosis of AD dementia, mild cognitive impairment (MCI) due to AD, prodromal AD and preclinical AD. As a consequence of matured research evidence six AD biomarkers are sufficiently validated and partly qualified to be incorporated into operationalized clinical diagnostic criteria and use in primary and secondary prevention trials. These biomarkers fall into two molecular categories: biomarkers of amyloid-beta (Aβ) deposition and plaque formation as well as of tau-protein related hyperphosphorylation and neurodegeneration. Three of the six gold-standard ("core feasible) biomarkers are neuroimaging measures and three are cerebrospinal fluid (CSF) analytes. CSF Aβ1-42 (Aβ1-42), also expressed as Aβ1-42 : Aβ1-40 ratio, T-tau, and P-tau Thr181 & Thr231 proteins have proven diagnostic accuracy and risk enhancement in prodromal MCI and AD dementia. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up. Magnetic resonance imaging (MRI) at increasing field strength and resolution allows detecting the evolution of distinct types of structural and functional abnormality pattern throughout early to late AD stages. Anatomical or volumetric MRI is the most widely used technique and provides local and global measures of atrophy. The revised diagnostic criteria for "prodromal AD" and "mild cognitive impairment due to AD" include hippocampal atrophy (as the fourth validated biomarker), which is considered an indicator of regional neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in regions of interest, such as the hippocampus and in an exploratory fashion, observer and hypothesis-indedendent, throughout the entire brain. Evolving modalities such as diffusion-tensor imaging (DTI) and advanced tractography as well as resting-state functional MRI provide useful additionally useful measures indicating the degree of fiber tract and neural network disintegration (structural, effective and functional connectivity) that may substantially contribute to early detection and the mapping of progression. These modalities require further standardization and validation. The use of molecular in vivo amyloid imaging agents (the fifth validated biomarker), such as the Pittsburgh Compound-B and markers of neurodegeneration, such as fluoro-2-deoxy-D-glucose (FDG) (as the sixth validated biomarker) support the detection of early AD pathological processes and associated neurodegeneration. How to use, interpret, and disclose biomarker results drives the need for optimized standardization. Multimodal AD biomarkers do not evolve in an identical manner but rather in a sequential but temporally overlapping fashion. Models of the temporal evolution of AD biomarkers can take the form of plots of biomarker severity (degree of abnormality) versus time. AD biomarkers can be combined to increase accuracy or risk. A list of genetic risk factors is increasingly included in secondary prevention trials to stratify and select individuals at genetic risk of AD. Although most of these biomarker candidates are not yet qualified and approved by regulatory authorities for their intended use in drug trials, they are nonetheless applied in ongoing clinical studies for the following functions: (i) inclusion/exclusion criteria, (ii) patient stratification, (iii) evaluation of treatment effect, (iv) drug target engagement, and (v) safety. Moreover, novel promising hypothesis-driven, as well as exploratory biochemical, genetic, electrophysiological, and neuroimaging markers for use in clinical trials are being developed. The current state-of-the-art and future perspectives on both biological and neuroimaging derived biomarker discovery and development as well as the intended application in prevention trials is outlined in the present publication.

Decreased coherence and functional connectivity of electroencephalograph in Alzheimer's disease

In this paper, we investigate the abnormalities of electroencephalograph (EEG) signals in the Alzheimer's disease (AD) by analyzing 16-scalp electrodes EEG signals and make a comparison with the normal controls. Coherence is introduced to measure the pair-wise normalized linear synchrony and functional correlations between two EEG signals in different frequency domains, and graph analysis is further used to investigate the influence of AD on the functional connectivity of human brain. Data analysis results show that, compared with the control group, the pair-wise coherence of AD group is significantly decreased, especially for the theta and alpha frequency bands in the frontal and parieto-occipital regions. Furthermore, functional connectivity among different brain regions is reconstructed based on EEG, which exhibit obvious small-world properties. Graph analysis demonstrates that the local functional connections between regions for AD decrease. In addition, it is found that small-world properties of AD networks are largely weakened, by calculating its average path lengths, clustering coefficients, global efficiency, local efficiency, and small-worldness. The obtained results show that both pair-wise coherence and functional network can be taken as effective measures to distinguish AD patients from the normal, which may benefit our understanding of the disease.

Assessment of the feasibility of a rehabilitation intervention program for breast cancer survivors with cognitive complaints

To assess the feasibility of a cognitive rehabilitation program in breast cancer survivors (BCS) with persistent post-treatment cognitive complaints. BCS with cognitive complaints, 18-months to 5-years post-treatment, were recruited for a once-weekly, five-week, group cognitive training intervention. Outcome measures included self-reported mood and cognitive function, and neurocognitive tests administered at pre-intervention, immediate-, two-month and four-month post-intervention. A sub-study in eight participants evaluated resting state quantitative electroencephalography (qEEG) changes from pre- to immediate post-intervention in relationship to post-intervention changes in cognitive complaints. Twenty-seven BCS completed the protocol and tolerated the intervention well. We observed significant reductions in total and memory-specific cognitive complaints from pre-intervention to immediate post-intervention (p = 0.031 and p = 0.009, respectively) and at four-months post-intervention (p < 0.0001 and p < 0.001, respectively). Significant improvement in neurocognitive tests were found for Symbol Digit, Stroop, and Trails A tests (df = 26, all p's <0.05). Effect sizes for changes from pre-intervention to immediate and to four-month post intervention ranged from 0.429 to 0.607, and from 0.439 to 0.741, respectively. Increase in qEEG absolute alpha power over the course of the intervention was associated with reduced complaints at immediate post-intervention (r = -0.78, p = 0.021), two-months (r range = -0.76 to -0.82, p-value range 0.004 to 0.03), and four-months (r = -0.71, p = 0.048). A five-week group cognitive training intervention is feasible and well tolerated. Cognitive complaints and neurocognitive test performances showed positive changes. qEEG may serve as a potential biomarker for improvement in self-reported complaints. A randomized clinical trial is underway to test the efficacy of the intervention.

Quantitative EEG markers relate to Alzheimer's disease severity in the Prospective Dementia Registry Austria (PRODEM)

OBJECTIVE

To investigate which single quantitative electro-encephalographic (QEEG) marker or which combination of markers correlates best with Alzheimer's disease (AD) severity as measured by the Mini-Mental State Examination (MMSE).

METHODS

We compared quantitative EEG markers for slowing (relative band powers), synchrony (coherence, canonical correlation, Granger causality) and complexity (auto-mutual information, Shannon/Tsallis entropy) in 118 AD patients from the multi-centric study PRODEM Austria. Signal spectra were determined using an indirect spectral estimator. Analyses were adjusted for age, sex, duration of dementia, and level of education.

RESULTS

For the whole group (39 possible, 79 probable AD cases) MMSE scores explained 33% of the variations in relative theta power during face encoding, and 31% of auto-mutual information in resting state with eyes closed. MMSE scores explained also 25% of the overall QEEG factor. This factor was thus subordinate to individual markers. In probable AD, QEEG coefficients of determination were always higher than in the whole group, where MMSE scores explained 51% of the variations in relative theta power.

CONCLUSIONS

Selected QEEG markers show strong associations with AD severity. Both cognitive and resting state should be used for QEEG assessments.

SIGNIFICANCE

Our data indicate theta power measured during face-name encoding to be most closely related to AD severity.

Temporo-frontal functional connectivity during auditory change detection is altered in Alzheimer's disease

Cortico-cortical connections might be disturbed in patients with Alzheimer's disease (AD). This study aimed to investigate the alterations of functional connectivity in AD during auditory change detection processing by measuring the local neuronal activation and functional connectivity between cortical regions. Magnetoencephalographic responses to deviant and standard sounds were recorded in 16 AD patients, 18 young controls and 16 elderly controls. Larger source amplitudes and shorter peak latencies were found in the right temporal magnetic mismatch responses of young controls compared with elderly controls and AD patients. During deviant stimuli, the right theta temporal-frontal phase synchrony was significantly smaller in AD than in young controls and elderly controls. Moreover, the left temporal-frontal synchronization at theta and alpha bands was reduced in AD and elderly controls compared with young controls. In conclusion, the loss in temporo-frontal theta synchronization might be an electrophysiological hallmark of AD.