Theta-power differences in patients with mild cognitive impairment under rest condition and during haptic tasks

Postoperative Delirium Severity and Recovery Correlate With Electroencephalogram Spectral Features

BACKGROUND

Delirium is an acute syndrome characterized by inattention, disorganized thinking, and an altered level of consciousness. A reliable biomarker for tracking delirium does not exist, but oscillations in the electroencephalogram (EEG) could address this need. We evaluated whether the frequencies of EEG oscillations are associated with delirium onset, severity, and recovery in the postoperative period.

METHODS

Twenty-six adults enrolled in the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES; ClinicalTrials.gov NCT02241655) study underwent major surgery requiring general anesthesia, and provided longitudinal postoperative EEG recordings for this prespecified substudy. The presence and severity of delirium were evaluated with the confusion assessment method (CAM) or the CAM-intensive care unit. EEG data obtained during awake eyes-open and eyes-closed states yielded relative power in the delta (1-4 Hz), theta (4-8 Hz), and alpha (8-13 Hz) bands. Discriminability for delirium presence was evaluated with c-statistics. To account for correlation among repeated measures within patients, mixed-effects models were generated to assess relationships between: (1) delirium severity and EEG relative power (ordinal), and (2) EEG relative power and time (linear). Slopes of ordinal and linear mixed-effects models are reported as the change in delirium severity score/change in EEG relative power, and the change in EEG relative power/time (days), respectively. Bonferroni correction was applied to confidence intervals (CIs) to account for multiple comparisons.

RESULTS

Occipital alpha relative power during eyes-closed states offered moderate discriminability (c-statistic, 0.75; 98% CI, 0.58-0.87), varying inversely with delirium severity (slope, -0.67; 98% CI, -1.36 to -0.01; P = .01) and with severity of inattention (slope, -1.44; 98% CI, -2.30 to -0.58; P = .002). Occipital theta relative power during eyes-open states correlated directly with severity of delirium (slope, 1.28; 98% CI, 0.12-2.44; P = .007), inattention (slope, 2.00; 98% CI, 0.48-3.54; P = .01), and disorganized thinking (slope, 3.15; 98% CI, 0.66-5.65; P = .01). Corresponding frontal EEG measures recapitulated these relationships to varying degrees. Severity of altered level of consciousness correlated with frontal theta relative power during eyes-open states (slope, 11.52; 98% CI, 6.33-16.71; P < .001). Frontal theta relative power during eyes-open states correlated inversely with time (slope, -0.05; 98% CI, -0.12 to -0.04; P = .002).

CONCLUSIONS

Presence, severity, and core features of postoperative delirium covary with spectral features of the EEG. The cost and accessibility of EEG facilitate the translation of these findings to future mechanistic and interventional trials.

Distinct Effects of the Apolipoprotein E ε4 Genotype on Associations Between Delayed Recall Performance and Resting-State Electroencephalography Theta Power in Elderly People Without Dementia

Background

Abnormal electroencephalography (EEG) activity has been demonstrated in mild cognitive impairment (MCI), and theta rhythm might be inversely related to memory. The apolipoprotein E (ApoE) epsilon 4 (ε4) allele, as a genetic vulnerability factor for pathologic and normal age-related cognitive decline, may influence different patterns of cognitive dysfunction. Therefore, the present study primarily aimed to verify the role of resting theta rhythm in delayed recall deficits, and further explore the effects of the ApoE genotype on the associations between the resting theta power and delayed recall performance in the elderly individuals without dementia.

Methods

A total of 47 individuals without dementia, including 23 MCI and 24 healthy subjects (HCs), participated in the study. All subjects were administered the Hopkins Verbal Learning Test–Revised (HVLT-R) to measure delayed recall performance. Power spectra based on resting-state EEG data were used to examine brain oscillations. Linear regression was used to examine the relationships between EEG power and delayed recall performance in each subgroup.

Results

The increased theta power in the bilateral central and temporal areas (P_s = 0.02–0.044, uncorrected) was found in the patients with MCI, and were negatively correlated with delayed recall performance (r_s = −0.358 to −0.306, P_s = 0.014–0.036, FDR corrected) in the elderly individuals without dementia. The worse delayed recall performance was associated with higher theta power in the left central and temporal areas, especially in ApoE ε4 non-carriers and not in carriers (r_s = −0.404 to −0.369, P_s = 0.02–0.035, uncorrected).

Conclusion

Our study suggests that theta disturbances might contribute to delayed recall memory decline. The ApoE genotype may have distinct effects on EEG-based neural correlates of episodic memory performance.

Disrupted Value-Directed Strategic Processing in Individuals with Mild Cognitive Impairment: Behavioral and Neural Correlates

Value-directed strategic processing involves attending to higher-value information while inhibiting lower-value information. This preferential processing is relatively preserved in cognitively normal older adults but is impaired in individuals with dementia. No studies have investigated whether value-directed strategic processing is disrupted in earlier stages of cognitive decline, namely, mild cognitive impairment (MCI). The current study examined behavioral and EEG differences in value-directed strategic processing between 18 individuals with MCI and 18 cognitively normal older controls using a value-directed list learning task. Behaviorally, individuals with MCI recalled fewer total and high-value words compared to controls, but no group differences were observed in low-value word recall. Neurally, individuals with MCI had reduced theta synchronization relative to controls between 100 and 200 ms post-stimulus. Greater alpha desynchronization was observed for high- versus low-value words between 300 and 400 ms in controls but not in the MCI group. The groups showed some processing similarities, with greater theta synchronization for low-value words between 700 and 800 ms and greater alpha desynchronization for high-value words between 500 and 1100 ms. Overall, value-directed strategic processing was compromised in individuals with MCI on both behavioral and neural measures relative to controls. These findings add to the growing body of literature on differences between typical cognitive aging and MCI.

Quantitative Electroencephalography Findings in Patients With Diabetes Mellitus

Objective. Diabetes mellitus (DM) causes structural central nervous system (CNS) impairment, and this situation can be detected by quantitative electroencephalography (QEEG) findings before cognitive impairment is clinically observed. The main aim of this study is to uncover the effect of DM on brain function. Since QEEG reflects the CNS functioning, particularly in cognitive aspects, we expected electrophysiological clues to be found for prevention and follow-up in DM-related cognitive decline. Since a majority of the psychiatric population have cognitive dysfunction, we have given particular attention to those people. It was stated that a decrease was observed in the posterior cortical alpha power due to the hippocampal atrophy by several previous studies and we hypothesize that decreased alpha power will be observed also in DM. Methods. This study included 2094 psychiatric patients, 207 of whom were diagnosed with DM and 1887 of whom were not diagnosed with DM, and QEEG recordings were performed. Eyes-closed electroencephalography data were segmented into consecutive 2 s epochs. Fourier analysis was performed by averaging across 2 s epochs without artifacts. The absolute alpha power in the occipital regions (O1 and O2) of patients with and without DM was compared. Results. In the DM group, a decrease in the absolute alpha, alpha 1, and alpha 2 power in O1 and O2 was observed in comparison with the control group. It was determined that the type of psychiatric diagnosis did not affect QEEG findings. Conclusion. The decrease in absolute alpha power observed in patients diagnosed with DM may be related to the CNS impairment in DM. QEEG findings in DM can be useful while monitoring the CNS impairment, diagnosing DM-related dementia, in the follow-up of the cognitive process, constructing the protocols for electrophysiological interventions like neurofeedback and transcranial magnetic stimulation and monitoring the response to treatment.

EEG/ERP evidence of possible hyperexcitability in older adults with elevated beta-amyloid

BACKGROUND

Although growing evidence links beta-amyloid (Aβ) and neuronal hyperexcitability in preclinical mouse models of Alzheimer's disease (AD), a similar association in humans is yet to be established. The first aim of the study was to determine the association between elevated Aβ (Aβ+) and cognitive processes measured by the P3 event-related potential (ERP) in cognitively normal (CN) older adults. The second aim was to compare the event-related power between CNAβ+ and CNAβ-.

METHODS

Seventeen CNAβ+ participants (age: 73 ± 5, 11 females, Montreal Cognitive Assessment [MoCA] score 26 ± 2) and 17 CNAβ- participants group-matched for age, sex, and MOCA completed a working memory task (n-back with n = 0, 1, 2) test while wearing a 256-channel electro-encephalography net. P3 peak amplitude and latency of the target, nontarget and task difference effect (nontarget-target), and event-related power in the delta, theta, alpha, and beta bands, extracted from Fz, Cz, and Pz, were compared between groups using linear mixed models. P3 amplitude of the task difference effect at Fz and event-related power in the delta band were considered main outcomes. Correlations of mean Aβ standard uptake value ratios (SUVR) using positron emission tomography with P3 amplitude and latency of the task difference effect were analyzed using Pearson Correlation Coefficient r.

RESULTS

The P3 peak amplitude of the task difference effect at Fz was lower in the CNAβ+ group (P = 0.048). Similarly, power was lower in the delta band for nontargets at Fz in the CNAβ+ participants (P = 0.04). The CNAβ+ participants also demonstrated higher theta and alpha power in channels at Cz and Pz, but no changes in P3 ERP. Strong correlations were found between the mean Aβ SUVR and the latency of the 1-back (r =  - 0.69; P = 0.003) and 2-back (r =  - 0.69; P = 0.004) of the task difference effect at channel Fz in the CNAβ+ group.

CONCLUSIONS

Our data suggest that the elevated amyloid in cognitively normal older adults is associated with neuronal hyperexcitability. The decreased P3 task difference likely reflects early impairments in working memory processes. Further research is warranted to determine the validity of ERP in predicting clinical, neurobiological, and functional manifestations of AD.

Sensory Dysfunction in Old Age

BACKGROUND

The senses serve as the crucial interface between the individual and the environment. They are subject to aging and disease processes.

METHODS

This review is based on pertinent publications retrieved by a selective search in the Medline and Cochrane Library databases.

RESULTS

Approximately 40% of persons aged 70 to 79 manifest dysfunction in at least one, and more than 25% in multiple senses. Sensory changes are accompanied by diverse comorbidities which depend on the particular sense(s) affected. The presence of sensory deficits is associated with an increased risk of developing dementia (OR: 1.49 [95% confidence interval: 1.12; 1.98] for dysfunction in a single sensory modality, 2.85 [1.88; 4.30] for dysfunction in three or more sensory modalities). The risk of developing depressive symptoms is elevated as well (OR 3.36 [2.28; 4.96]). The individual's ability to cope with the demands of everyday life is largely determined by the ability to carry out multisensory integration, in which the perceptions of the different senses are bound together. This function itself is subject to age-related changes that can be either adaptive or maladaptive; it can, therefore, serve as an indicator for pathological aging processes.

CONCLUSION

Sensory dysfunction in old age should be detected as early as possible. This implies the need for close collaboration of all of the involved disciplines. It would be desirable to develop sensory screening tests as well as a procedure for testing multisensory integration in routine clinical practice.

MCI Detection Using Kernel Eigen-Relative-Power Features of EEG Signals

Classification between individuals with mild cognitive impairment (MCI) and healthy controls (HC) based on electroencephalography (EEG) has been considered a challenging task to be addressed for the purpose of its early detection. In this study, we proposed a novel EEG feature, the kernel eigen-relative-power (KERP) feature, for achieving high classification accuracy of MCI versus HC. First, we introduced the relative powers (RPs) between pairs of electrodes across 21 different subbands of 2-Hz width as the features, which have not yet been used in previous MCI-HC classification studies. Next, the Fisher’s class separability criterion was applied to determine the best electrode pairs (five electrodes) as well as the frequency subbands for extracting the most sensitive RP features. The kernel principal component analysis (kernel PCA) algorithm was further performed to extract a few more discriminating nonlinear principal components from the optimal RPs, and these components form a KERP feature vector. Results carried out on 51 participants (24 MCI and 27 HC) show that the newly introduced subband RP feature showed superior classification performance to commonly used spectral power features, including the band power, single-electrode relative power, and also the RP based on the conventional frequency bands. A high leave-one-participant-out cross-validation (LOPO-CV) classification accuracy 86.27% was achieved by the RP feature, using a simple linear discriminant analysis (LDA) classifier. Moreover, with the same classifier, the proposed KERP further improved the accuracy to 88.24%. Finally, cascading the KERP feature to a nonlinear classifier, the support vector machine (SVM), yields a high MCI-HC classification accuracy of 90.20% (sensitivity = 87.50% and specificity = 92.59%). The proposed method demonstrated a high accuracy and a high usability (only five electrodes are required), and therefore, has great potential to further develop an EEG-based computer-aided diagnosis system that can be applied for the early detection of MCI.

Abnormalities in auditory and visual cognitive processes are differentiated with theta responses in patients with Parkinson's disease with and without dementia

The research on the abnormalities of event-related oscillations in Parkinson's disease (PD) was mostly studied with cognitively normal patients. The present study aims to show the adverse effects of cognitive decline in PD patients via the EEG-Brain Oscillations approach by comparing the electrophysiological responses in two modalities, i.e. auditory, and visual in which PD group show deficit. We conducted a study in which we analyzed event-related theta power and phase-locking during auditory and visual oddball paradigm. Cognitively normal PD (PDCN) patients (N = 15), PD with mild cognitive impairment (PDMCI) patients (N = 22), PD dementia (PDD) patients (N = 11) and healthy controls (HC) (N = 17) were included in the study. Neuropsychological assessments were applied to all participants. There was a gradual decrease in scores of neuropsychological tests (HC, PDCN, PDMCI, PDD, respectively). Most of the neuropsychological test scores of the participants were highly correlated with the theta power and theta phase locking values, especially over frontal-central areas. HC had higher theta phase-locking and power in comparison to PDMCI and PDD. The differentiation between HC and PDCN was specific to frontal-central areas. Theta power and theta phase-locking were decreased overall locations in PDMCI and PDD both during visual and auditory oddball paradigms compared with PDCN. The results indicate that theta responses in PD patients decreased gradually as the cognitive decline increased. We can conclude that complex abnormalities in their neurotransmitter and neuronal signal systems that occur with the progression of the disease could be responsible for these results.

Global EEG coherence as a marker for cognition in older adults at risk for dementia

Quantitative electroencephalography (EEG) provides useful information about neurophysiological health of the aging brain. Current studies investigating EEG coherence and power for specific brain areas and frequency bands have yielded inconsistent results. This study assessed EEG coherence and power indices at rest measured over the whole skull and for a wide frequency range as global EEG markers for cognition in a sample at risk for dementia. Since global markers are more reliable and less error-prone than region- and frequency-specific indices they might help to overcome previous inconsistencies. Global EEG coherence (1-30 Hz) and an EEG slowing score were assessed. The EEG slowing score was calculated by low-frequency power (1-8 Hz) divided by high-frequency power (9-30 Hz). In addition, the prognostic value of the two EEG indices for cognition and cognitive decline was assessed in a 5-year follow-up pilot study. Baseline global coherence correlated positively with cognition at baseline, but not with cognitive decline or with cognition at the 5-year follow-up. The EEG slowing ratio showed no significant association, neither with cognition at baseline or follow-up, nor with cognitive decline over a period of 5 years. The results indicate that the resting state global EEG coherence might be a useful and easy to assess electrophysiological correlate for neurocognitive health in older adults at risk for dementia. Because of the small statistical power for the follow-up analyses, the prognostic value of global coherence could not be determined in the present study. Future studies should assess its prognostic value with larger sample sizes.

Visuo-Haptic Exploration for Multimodal Memory

When faced with a novel object, we explore it to understand its shape. This way we combine information coming from different senses, as touch, proprioception and vision, together with the motor information embedded in our motor execution plan. The exploration process provides a structure and constrains this rich flow of inputs, supporting the formation of a unified percept and the memorization of the object features. However, how the exploration strategies are planned is still an open question. In particular, is the exploration strategy used to memorize an object different from the exploration strategy adopted in a recall task? To address this question we used iCube, a sensorized cube which measures its orientation in space and the location of the contacts on its faces. Participants were required to explore the cube faces where little pins were positioned in varying number. Participants had to explore the cube twice and individuate potential differences between the two presentations, which could be performed either haptically alone, or with also vision available. The haptic and visuo-haptic (VH) exploratory strategies changed significantly when finalized to memorize the structure of the object with respect to when the same object was explored to recall and compare it with its memorized instance. These findings indicate that exploratory strategies are adapted not only to the property of the object to be analyzed but also to the prospective use of the resulting representation, be it memorization or recall. The results are discussed in light of the possibility of a systematic modeling of natural VH exploration strategies.

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.

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.

Theta and Alpha Alterations in Amnestic Mild Cognitive Impairment in Semantic Go/NoGo Tasks

Growing evidence suggests that cognitive control processes are impaired in amnestic mild cognitive impairment (aMCI); however the nature of these alterations needs further examination. The current study examined differences in electroencephalographic theta and alpha power related to cognitive control processes involving response execution and response inhibition in 22 individuals with aMCI and 22 age-, sex-, and education-matched cognitively normal controls. Two Go/NoGo tasks involving semantic categorization were used. In the basic categorization task, Go/NoGo responses were made based on exemplars of a single car (Go) and a single dog (NoGo). In the superordinate categorization task, responses were made based on multiple exemplars of objects (Go) and animals (NoGo). Behavioral data showed that the aMCI group had more false alarms during the NoGo trials compared to controls. The EEG data revealed between group differences related to response type in theta (4–7 Hz) and low-frequency alpha (8–10 Hz) power. In particular, the aMCI group differed from controls in theta power during the NoGo trials at frontal and parietal electrodes, and in low-frequency alpha power during Go trials at parietal electrodes. These results suggest that alterations in theta power converge with behavioral deterioration in response inhibition, whereas alterations in low-frequency alpha power appear to precede behavioral changes in response execution. Both behavioral and electrophysiological correlates combined provide a more comprehensive characterization of cognitive control deficits in aMCI.

Resting-State Subjective Experience and EEG Biomarkers Are Associated with Sleep-Onset Latency

Difficulties initiating sleep are common in several disorders, including insomnia and attention deficit hyperactivity disorder. These disorders are prevalent, bearing significant societal and financial costs which require the consideration of new treatment strategies and a better understanding of the physiological and cognitive processes surrounding the time of preparing for sleep or falling asleep. Here, we search for neuro-cognitive associations in the resting state and examine their relevance for predicting sleep-onset latency using multi-level mixed models. Multiple EEG recordings were obtained from healthy male participants (N = 13) during a series of 5 min eyes-closed resting-state trials (in total, n = 223) followed by a period-varying in length up to 30 min-that either allowed subjects to transition into sleep ("sleep trials," n sleep = 144) or was ended while they were still awake ("wake trials," n wake = 79). After both eyes-closed rest, sleep and wake trials, subjective experience was assessed using the Amsterdam Resting-State Questionnaire (ARSQ). Our data revealed multiple associations between eyes-closed rest alpha and theta oscillations and ARSQ-dimensions Discontinuity of Mind, Self, Theory of Mind, Planning, and Sleepiness. The sleep trials showed that the transition toward the first sleep stage exclusively affected subjective experiences related to Theory of Mind, Planning, and Sleepiness. Importantly, sleep-onset latency was negatively associated both with eyes-closed rest ratings on the ARSQ dimension of Sleepiness and with the long-range temporal correlations of parietal theta oscillations derived by detrended fluctuation analysis (DFA). These results could be relevant to the development of personalized tools that help evaluate the success of falling asleep based on measures of resting-state cognition and EEG biomarkers.

Quantitative EEG of Rapid-Eye-Movement Sleep: A Marker of Amnestic Mild Cognitive Impairment

The basal forebrain cholinergic system, which is impaired in early Alzheimer's disease, is more crucial for the activation of rapid-eye-movement (REM) sleep electroencephalogram (EEG) than it is for wakefulness. Quantitative EEG from REM sleep might thus provide an earlier and more accurate marker of the development of Alzheimer's disease in subjects with mild cognitive impairment (MCI) subjects than that from wakefulness. To assess the superiority of the REM sleep EEG as a screening tool for preclinical Alzheimer's disease, 22 subjects with amnestic MCI (a-MCI; 63.9±7.7 years), 10 subjects with nonamnestic MCI (na-MCI; 64.1±4.5 years) and 32 controls (63.7±6.6 years) participated in the study. Spectral analyses of the waking EEG and REM sleep EEG were performed and the [(delta+theta)/(alpha+beta)] ratio was used to assess between-group differences in EEG slowing. The a-MCI subgroup showed EEG slowing in frontal lateral regions compared to both na-MCI and control groups. This EEG slowing was present in wakefulness (compared to controls) but was much more prominent in REM sleep. Moreover, the comparison between amnestic and nonamnestic subjects was found significant only for the REM sleep EEG. There was no difference in EEG power ratio between na-MCI and controls for any of the 7 cortical regions studied. These findings demonstrate the superiority of the REM sleep EEG in the discrimination between a-MCI and both na-MCI and control subjects.

Precocious Alterations of Brain Oscillatory Activity in Alzheimer's Disease: A Window of Opportunity for Early Diagnosis and Treatment

Alzheimer's disease (AD) is the most common form of neurodegenerative dementia accounting for 50-80% of all age-related dementia. This pathology is characterized by the progressive and irreversible alteration of cognitive functions, such as memory, leading inexorably to the loss of autonomy for patients with AD. The pathology is linked with aging and occurs most commonly around 65 years old. Its prevalence (5% over 65 years of age and 20% after 80 years) constitutes an economic and social burden for AD patients and their family. At the present, there is still no cure for AD, actual treatments being moderately effective only in early stages of the pathology. A lot of efforts have been deployed with the aim of defining new AD biomarkers. Successful early detection of mild cognitive impairment (MCI) linked to AD requires the identification of biomarkers capable of distinguishing individuals with early stages of AD from other pathologies impacting cognition such as depression. In this article, we will review recent evidence suggesting that electroencephalographic (EEG) recordings, coupled with behavioral assessments, could be a useful approach and easily implementable for a precocious detection of AD.

Distinguishing rhythmic from non-rhythmic brain activity during rest in healthy neurocognitive aging

Rhythmic brain activity at low frequencies (<12Hz) during rest are thought to increase in neurodegenerative disease, but findings in healthy neurocognitive aging are mixed. Here we address two reasons conventional spectral analyses may have led to inconsistent results. First, spectral-power measures are compared to a baseline condition; when resting activity is the signal of interest, it is unclear what the baseline should be. Second, conventional methods do not clearly differentiate power due to rhythmic versus non-rhythmic activity. The Better OSCillation detection method (BOSC; Caplan et al., 2001; Whitten et al., 2011) avoids these problems by using the signal's own spectral characteristics as a reference to detect elevations in power lasting a few cycles. We recorded electroencephalographic (EEG) signal during rest, alternating eyes open and closed, in healthy younger (18-25 years) and older (60-74 years) participants. Topographic plots suggested the conventional and BOSC analyses measured different sources of activity, particularly at frequencies, like delta (1-4Hz), at which rhythms are sporadic; topographies were more similar in the 8-12Hz alpha band. There was little theta-band activity meeting the BOSC method's criteria, suggesting prior findings of theta power in healthy aging may reflect non-rhythmic signal. In contrast, delta oscillations were present at higher levels than theta in both age groups. In summary, applying strict and standardized criteria for rhythmicity, slow rhythms appear present in the resting brain at delta and alpha, but not theta frequencies, and appear unchanged in healthy aging.

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.

MEG spectral analysis in subtypes of mild cognitive impairment

Mild cognitive impairment (MCI) has been described as an intermediate stage between normal aging and dementia. Previous studies characterized the alterations of brain oscillatory activity at this stage, but little is known about the differences between single and multidomain amnestic MCI patients. In order to study the patterns of oscillatory magnetic activity in amnestic MCI subtypes, a total of 105 subjects underwent an eyes-closed resting-state magnetoencephalographic recording: 36 healthy controls, 33 amnestic single domain MCIs (a-sd-MCI), and 36 amnestic multidomain MCIs (a-md-MCI). Relative power values were calculated and compared among groups. Subsequently, relative power values were correlated with neuropsychological tests scores and hippocampal volumes. Both MCI groups showed an increase in relative power in lower frequency bands (delta and theta frequency ranges) and a decrease in power values in higher frequency bands (alpha and beta frequency ranges), as compared with the control group. More importantly, clear differences emerged from the comparison between the two amnestic MCI subtypes. The a-md-MCI group showed a significant power increase within delta and theta ranges and reduced relative power within alpha and beta ranges. Such pattern correlated with the neuropsychological performance, indicating that the a-md-MCI subtype is associated not only with a "slowing" of the spectrum but also with a poorer cognitive status. These results suggest that a-md-MCI patients are characterized by a brain activity profile that is closer to that observed in Alzheimer disease. Therefore, it might be hypothesized that the likelihood of conversion to dementia would be higher within this subtype.

Human haptic perception is interrupted by explorative stops of milliseconds

INTRODUCTION

The explorative scanning movements of the hands have been compared to those of the eyes. The visual process is known to be composed of alternating phases of saccadic eye movements and fixation pauses. Descriptive results suggest that during the haptic exploration of objects short movement pauses occur as well. The goal of the present study was to detect these "explorative stops" (ES) during one-handed and two-handed haptic explorations of various objects and patterns, and to measure their duration. Additionally, the associations between the following variables were analyzed: (a) between mean exploration time and duration of ES, (b) between certain stimulus features and ES frequency, and (c) the duration of ES during the course of exploration.

METHODS

Five different Experiments were used. The first two Experiments were classical recognition tasks of unknown haptic stimuli (A) and of common objects (B). In Experiment C space-position information of angle legs had to be perceived and reproduced. For Experiments D and E the PHANToM haptic device was used for the exploration of virtual (D) and real (E) sunken reliefs.

RESULTS

In each Experiment we observed explorative stops of different average durations. For Experiment A: 329.50 ms, Experiment B: 67.47 ms, Experiment C: 189.92 ms, Experiment D: 186.17 ms and Experiment E: 140.02 ms. Significant correlations were observed between exploration time and the duration of the ES. Also, ES occurred more frequently, but not exclusively, at defined stimulus features like corners, curves and the endpoints of lines. However, explorative stops do not occur every time a stimulus feature is explored.

CONCLUSIONS

We assume that ES are a general aspect of human haptic exploration processes. We have tried to interpret the occurrence and duration of ES with respect to the Hypotheses-Rebuild-Model and the Limited Capacity Control System theory.

The Amsterdam Resting-State Questionnaire reveals multiple phenotypes of resting-state cognition

Resting-state neuroimaging is a dominant paradigm for studying brain function in health and disease. It is attractive for clinical research because of its simplicity for patients, straightforward standardization, and sensitivity to brain disorders. Importantly, non-sensory experiences like mind wandering may arise from ongoing brain activity. However, little is known about the link between ongoing brain activity and cognition, as phenotypes of resting-state cognition-and tools to quantify them-have been lacking. To facilitate rapid and structured measurements of resting-state cognition we developed a 50-item self-report survey, the Amsterdam Resting-State Questionnaire (ARSQ). Based on ARSQ data from 813 participants assessed after 5 min eyes-closed rest in their home, we identified seven dimensions of resting-state cognition using factor analysis: Discontinuity of Mind, Theory of Mind, Self, Planning, Sleepiness, Comfort, and Somatic Awareness. Further, we showed that the structure of cognition was similar during resting-state fMRI and EEG, and that the test-retest correlations were remarkably high for all dimensions. To explore whether inter-individual variation of resting-state cognition is related to health status, we correlated ARSQ-derived factor scores with psychometric scales measuring depression, anxiety, and sleep quality. Mental health correlated positively with Comfort and negatively with Discontinuity of Mind. Finally, we show that sleepiness may partially explain a resting-state EEG profile previously associated with Alzheimer's disease. These findings indicate that the ARSQ readily provides information about cognitive phenotypes and that it is a promising tool for research on the neural correlates of resting-state cognition in health and disease.

Magnetoencephalography as a putative biomarker for Alzheimer's disease

Alzheimer's Disease (AD) is the most common dementia in the elderly and is estimated to affect tens of millions of people worldwide. AD is believed to have a prodromal stage lasting ten or more years. While amyloid deposits, tau filaments, and loss of brain cells are characteristics of the disease, the loss of dendritic spines and of synapses predate such changes. Popular preclinical detection strategies mainly involve cerebrospinal fluid biomarkers, magnetic resonance imaging, metabolic PET scans, and amyloid imaging. One strategy missing from this list involves neurophysiological measures, which might be more sensitive to detect alterations in brain function. The Magnetoencephalography International Consortium of Alzheimer's Disease arose out of the need to advance the use of Magnetoencephalography (MEG), as a tool in AD and pre-AD research. This paper presents a framework for using MEG in dementia research, and for short-term research priorities.

Complexity analysis of spontaneous brain activity in Alzheimer disease and mild cognitive impairment: an MEG study

Nonlinear analyses have shown that Alzheimer disease (AD) patients' brain activity is characterized by a reduced complexity and connectivity. The aim of this study is to define complexity patterns of mild cognitive impairment (MCI) patients. Whole-head magnetoencephalography recordings were obtained from 18 diagnosed AD patients, 18 MCI patients, and 18 healthy controls during resting conditions. Lempel-Ziv complexity (LZC) values were calculated. MCI patients exhibited intermediary LZC scores between AD patients and controls. A combination of age and posterior LZC scores allowed ADs-MCIs discrimination with 94.4% sensitivity and specificity, whereas no LZC score allowed MCIs---controls discrimination. AD patients and controls showed a parallel tendency to diminished LZC scores as a function of age, but MCI patients did not exhibit such "normal" tendency. Accordingly, anterior LZC scores allowed MCIs-controls discrimination for subjects below 75 years. MCIs exhibited a qualitatively distinct relationship between aging and complexity reduction, with scores higher than controls in older individuals. This fact might be considered a new example of compensatory mechanism in MCI before fully established dementia.

EEG Patterns in Mild Cognitive Impairment (MCI) Patients

An emerging clinical priority for the treatment of Alzheimer's disease (AD) is the implementation of therapies at the earliest stages of disease onset. All AD patients pass through an intermediary stage of the disorder known as Mild Cognitive Impairment (MCI), but not all patients with MCI develop AD. By applying computer based signal processing and pattern recognition techniques to the electroencephalogram (EEG), we were able to classify AD patients versus controls with an accuracy rate of greater than 80%. We were also able to categorize MCI patients into two subgroups: those with EEG Beta power profiles resembling AD patients and those more like controls. We then used this brain-based classification to make predictions regarding those MCI patients most likely to progress to AD versus those who would not. Our classification algorithm correctly predicted the clinical status of 4 out of 6 MCI patients returning for 2 year clinical follow-up. While preliminary in nature, our results suggest that automated pattern recognition techniques applied to the EEG may be a useful clinical tool not only for classification of AD patients versus controls, but also for identifying those MCI patients most likely to progress to AD.

EEG Patterns in Mild Cognitive Impairment (MCI) Patients

An emerging clinical priority for the treatment of Alzheimer’s disease (AD) is the implementation of therapies at the earliest stages of disease onset. All AD patients pass through an intermediary stage of the disorder known as Mild Cognitive Impairment (MCI), but not all patients with MCI develop AD. By applying computer based signal processing and pattern recognition techniques to the electroencephalogram (EEG), we were able to classify AD patients versus controls with an accuracy rate of greater than 80%. We were also able to categorize MCI patients into two subgroups: those with EEG Beta power profiles resembling AD patients and those more like controls. We then used this brain-based classification to make predictions regarding those MCI patients most likely to progress to AD versus those who would not. Our classification algorithm correctly predicted the clinical status of 4 out of 6 MCI patients returning for 2 year clinical follow-up. While preliminary in nature, our results suggest that automated pattern recognition techniques applied to the EEG may be a useful clinical tool not only for classification of AD patients versus controls, but also for identifying those MCI patients most likely to progress to AD.

Abnormal-induced theta activity supports early directed-attention network deficits in progressive MCI

The electroencephalography (EEG) theta frequency band reacts to memory and selective attention paradigms. Global theta oscillatory activity includes a posterior phase-locked component related to stimulus processing and a frontal-induced component modulated by directed attention. To investigate the presence of early deficits in the directed attention-related network in elderly individuals with mild cognitive impairment (MCI), time-frequency analysis at baseline was used to assess global and induced theta oscillatory activity (4-6Hz) during n-back working memory tasks in 29 individuals with MCI and 24 elderly controls (EC). At 1-year follow-up, 13 MCI patients were still stable and 16 had progressed. Baseline task performance was similar in stable and progressive MCI cases. Induced theta activity at baseline was significantly reduced in progressive MCI as compared to EC and stable MCI in all n-back tasks, which were similar in terms of directed attention requirements. While performance is maintained, the decrease of induced theta activity suggests early deficits in the directed-attention network in progressive MCI, whereas this network is functionally preserved in stable MCI.

Working memory load-related electroencephalographic parameters can differentiate progressive from stable mild cognitive impairment

Recent studies described several changes of endogenous event-related potentials (ERP) and brain rhythm synchronization during memory activation in patients with Alzheimer's disease (AD). To examine whether memory-related EEG parameters may predict cognitive decline in mild cognitive impairment (MCI), we assessed P200 and N200 latencies as well as beta event-related synchronization (ERS) in 16 elderly controls (EC), 29 MCI cases and 10 patients with AD during the successful performance of a pure attentional detection task as compared with a highly working memory demanding two-back task. At 1 year follow-up, 16 MCI patients showed progressive cognitive decline (PMCI) and 13 remained stable (SMCI). Both P200 and N200 latencies in the two-back task were longer in PMCI and AD cases compared with EC and SMCI cases. During the interval 1000 ms to 1700 ms after stimulus, beta ERS at parietal electrodes was of lower amplitude in PMCI and AD compared with EC and SMCI cases. Univariate models showed that P200, N200 and log% beta values were significantly related to the SMCI/PMCI distinction with areas under the receiver operating characteristic curve of 0.93, 0.78 and 0.72, respectively. The combination of all three EEG hallmarks was the stronger predictor of MCI deterioration with 90% of correctly classified MCI cases. Our data reveal that PMCI and clinically overt AD share the same pattern of working memory-related EEG activation characterized by increased P200-N200 latencies and decreased beta ERS. They also show that P200 latency during the two-back task may be a simple and promising EEG marker of rapid cognitive decline in MCI.

Changes of EEG spectra and coherence following performance in a cognitive task in Alzheimer's disease

Electroencephalographic measures combined with cognitive tasks are widely used for the assessment of cognitive and pathophysiological changes in Alzheimer's disease (AD). Instead of the analysis of EEG data obtained during the performance of the task, in this study data recorded in the immediate after-task period were analyzed. It was expected that this period would correspond to the electrophysiological consequences of the cognitive effort. Data of 14 patients with AD (MMS score: 16-24) were compared to that of 10 healthy control subjects. Reverse counting of a fix duration was used as a cognitive task. Changes of relative frequency spectra, and those of inter-and intrahemispheric coherence were analyzed. Relative theta power was significantly higher in AD patients compared to the controls both before and after the task. The performance of the task resulted in an increase of the relative alpha2 band in the AD group, whereas it slightly decreased in the control group. The most prominent coherence differences between AD and controls were found in the alpha1 band, especially for long-range coherence values. Coherence in this frequency band increased in the control group following the task, not seen in the AD group. We conclude that EEG parameters calculated from epochs following the completion of a cognitive task clearly differentiates patients with AD from normal controls. The electrophysiological changes found in AD may correspond to the decrease of functional connectivity of cortical areas and to the malfunctioning of the networks engaged in the cognitive task investigated.

Does the Hippocampal Atrophy Correlate With the Cortical Theta Power in Elderly Subjects With a Range of Cognitive Impairment?

A previous study with a small sample (N = 39) showed a significant correlation between the cortical theta activity and the hippocampal volume in different stages of cognitive impairment in aged subjects. The recent study was aimed to replicate these results in a much bigger sample. The authors examined a sample of 121 right-handed subjects. The sample consisted of 37 healthy controls, 40 patients with questionable dementia, and 44 patients with mild dementia assessed by Clinical Dementia Rating. All subjects underwent EEG and brain MRI. Mean spectral power was calculated, and volume of hippocampal segments was measured. EEG theta power of the left and right hemisphere correlated significantly with the hippocampal volume on the left and right side in different stages of cognitive impairment. An increase of theta power was associated with decreased hippocampal volume. No other significant correlations were found for alpha or beta band power. No correlation was found between cortical theta and global brain volume. There seems to be a direct relationship between neuronal loss of the hippocampus and changed cortical theta activity for different stages of cognitive impairment in aged subjects.

Memory activation enhances EEG abnormality in mild cognitive impairment

This exploratory study investigated EEG power changes during memory activation in patients with amnestic mild cognitive impairment (MCI). Twelve MCI patients and 16 age-matched controls underwent EEG registration during two conventional EEG conditions ('eyes closed' and 'eyes open') and three memory conditions ('word memory', 'picture memory' and 'animal fluency'). For all conditions, EEG power in the theta (4-8 Hz), lower alpha (8-10.5 Hz) and upper alpha (10.5-13 Hz) bands were expressed as percentile changes compared to 'eyes closed'. MCI patients showed significantly less decrease in the lower alpha band than controls (p=0.04) during picture memory activation. The word memory task showed a trend towards a similar effect (p=0.09). This study suggests that memory activation reveals EEG differences between MCI patients and controls while conventional EEG conditions do not.

Decreased theta event-related synchronization during working memory activation is associated with progressive mild cognitive impairment

BACKGROUND

Among the different quantitative electroencephalographic markers, theta activity is known to reflect neural resources involved in memory processes and directed attention. Previous studies suggested that synchronization likelihood analysis in theta-band frequency might be a sensitive method to identify early alterations of neuronal networks in mild cognitive impairment (MCI).

METHODS

We report here a longitudinal study of 24 MCI patients with theta event-related synchronization (ERS) analysis during the n-back working memory task and neuropsychological follow-up after 1 year. Statistical analysis included analysis of variance and logistic regression to assess the relationship between cognitive decline and theta ERS.

RESULTS

Upon follow-up, 13 MCI patients showed progressive MCI and 11 remained stable. In both groups, the phasic increase in theta amplitude after stimulus presentation did not depend on working memory load and electrode sites. Progressive MCI cases displayed significantly lower theta ERS power over all electrode sites compared to stable MCI cases. Theta ERS was significantly related to the cognitive outcome explaining 15.5% of its variability. In terms of MCI classification, the best combination of sensitivity and specificity was 0.87 and 0.60, respectively, with an area under the corresponding receiver operating characteristic curve reaching 76%.

CONCLUSIONS

The present data indicate that a decrease in the early phasic theta ERS power during working memory activation may predict cognitive decline in MCI. This phenomenon is not related to working memory load but may reflect the presence of early deficits in directed attention-related neural circuits in MCI.

Sources of cortical rhythms in adults during physiological aging: a multicentric EEG study

This electroencephalographic (EEG) study tested whether cortical EEG rhythms (especially delta and alpha) show a progressive increasing or decreasing trend across physiological aging. To this aim, we analyzed the type of correlation (linear and nonlinear) between cortical EEG rhythms and age. Resting eyes-closed EEG data were recorded in 108 young (Nyoung; age range: 18-50 years, mean age 27.3+/-7.3 SD) and 107 elderly (Nold; age range: 51-85 years, mean age 67.3+/-9.2 SD) subjects. The EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Statistical results showed that delta sources in the occipital area had significantly less magnitude in Nold compared to Nyoung subjects. Similarly, alpha 1 and alpha 2 sources in the parietal, occipital, temporal, and limbic areas had significantly less magnitude in Nold compared to Nyoung subjects. These nine EEG sources were given as input for evaluating the type (linear, exponential, logarithmic, and power) of correlation with age. When subjects were considered as a single group there was a significant linear correlation of age with the magnitude of delta sources in the occipital area and of alpha 1 sources in occipital and limbic areas. The same was true for alpha 2 sources in the parietal, occipital, temporal, and limbic areas. In general, the EEG sources showing significant linear correlation with age also supported a nonlinear correlation with age. These results suggest that the occipital delta and posterior cortical alpha rhythms decrease in magnitude during physiological aging with both linear and nonlinear trends. In conclusion, this new methodological approach holds promise for the prediction of dementia in mild cognitive impairment by regional source rather than surface EEG data and by both linear and nonlinear predictors.

MEG spectral profile in Alzheimer's disease and mild cognitive impairment

OBJECTIVE

In this study, we applied a novel procedure to calculate the mean frequency from the Magnetoencephalography (MEG) signals of 22 patients with Alzheimer's Disease (AD), 22 patients with mild cognitive impairment (MCI), and 21 healthy controls. A significant mean frequency decrease was expected in pathological groups. MCI subjects are expected to show intermediate mean frequency values between AD patients and controls.

METHODS

MEG signal was obtained from a whole-head 148 channels magnetometer in a resting condition. We estimated the power spectral density from the MEG signal by means of the Fourier transform of the autocorrelation function. Then, we computed the mean frequency for each subject.

RESULTS

Mean frequency was higher in controls (12.46 +/- 2.00 Hz, mean +/- SD) than in MCI subjects (10.82 +/- 2.21 Hz) with significant differences (P < 0.05). Moreover, mean frequency values in MCI subjects were higher than in AD patients (9.06 +/- 2.48 Hz, P < 0.05). We also detected a decrease of 0.17 Hz per year in mean frequency from normal subjects' MEG (P < 0.05)

CONCLUSIONS

Results demonstrated that the approach adopted for the calculation of a mean frequency score seems to be adequate and sensitive to detect differences between normal aging, cognitive deterioration and AD. In addition, data may contribute to the theoretical discussion on the nature of mild cognitive impairment and its similitudes with Alzheimer's disease.

SIGNIFICANCE

This paper may be considered a first step to obtain a reliable measure which summarizes spectral information, and might be of a potential clinical interest.

Sources of cortical rhythms change as a function of cognitive impairment in pathological aging: a multicenter study

OBJECTIVE

The present study tested the hypothesis that cortical electroencephalographic (EEG) rhythms. change across normal elderly (Nold), mild cognitive impairment (MCI), and Alzheimer's disease (AD) subjects as a function of the global cognitive level.

METHODS

Resting eyes-closed EEG data were recorded in 155 MCI, 193 mild AD, and 126 age-matched Nold subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by LORETA.

RESULTS

Occipital delta and alpha 1 sources in parietal, occipital, temporal, and 'limbic' areas had an intermediate magnitude in MCI subjects compared to mild AD and Nold subjects. These five EEG sources presented both linear and nonlinear (linear, exponential, logarithmic, and power) correlations with the global cognitive level (as revealed by mini mental state examination score) across all subjects.

CONCLUSIONS

Cortical EEG rhythms change in pathological aging as a function of the global cognitive level.

SIGNIFICANCE

The present functional data on large populations support the 'transitional hypothesis' of a shadow zone across normality, pre-clinical stage of dementia (MCI), and AD.

Apolipoprotein E and alpha brain rhythms in mild cognitive impairment: A multicentric Electroencephalogram study

OBJECTIVE

Relationships between the apolipoprotein E epsilon4 allele and electroencephalographic (EEG) rhythmicity have been demonstrated in Alzheimer's disease (AD) patients but not in the preclinical stage prodromic to it, namely, mild cognitive impairment (MCI). The present multicentric EEG study tested the hypothesis that presence of epsilon4 affects sources of resting EEG rhythms in both MCI and AD subjects.

METHODS

We enrolled 89 MCI subjects (34.8% with epsilon4) and 103 AD patients (50.4% with epsilon4). Resting eyes-closed EEG data were recorded for all subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography.

RESULTS

Results showed that amplitude of alpha 1 and 2 sources in occipital, temporal, and limbic areas was lower in subjects carrying the epsilon4 allele than in those not carrying the epsilon4 allele (p < 0.01). This was true for both MCI and AD. For the first time to our knowledge, a relationship was shown between ApoE genotype and global neurophysiological phenotype (ie, cortical alpha rhythmicity) in a preclinical AD condition, MCI, in addition to clinically manifest AD.

INTERPRETATION

Such a demonstration motivates future genotype-EEG phenotype studies for the early prediction of AD conversion in individual MCI subjects.

Fronto-parietal coupling of brain rhythms in mild cognitive impairment: a multicentric EEG study

Electroencephalographic (EEG) data were recorded in 69 normal elderly (Nold), 88 mild cognitive impairment (MCI), and 109 mild Alzheimer's disease (AD) subjects at rest condition, to test whether the fronto-parietal coupling of EEG rhythms is in line with the hypothesis that MCI can be considered as a pre-clinical stage of the disease at group level. Functional coupling was estimated by synchronization likelihood of Laplacian-transformed EEG data at electrode pairs, which accounts for linear and non-linear components of that coupling. Cortical rhythms of interest were delta (2-4Hz), theta (4-8Hz), alpha 1 (8-10.5Hz), alpha 2 (10.5-13Hz), beta 1 (13-20Hz), beta 2 (20-30Hz), and gamma (30-40Hz). Compared to the Nold subjects, the AD patients presented a marked reduction of the synchronization likelihood (delta to gamma) at both fronto-parietal and inter-hemispherical (delta to beta 2) electrodes. As a main result, alpha 1 synchronization likelihood progressively decreased across Nold, MCI, and mild AD subjects at midline (Fz-Pz) and right (F4-P4) fronto-parietal electrodes. The same was true for the delta synchronization likelihood at right fronto-parietal electrodes (F4-P4). For these EEG bands, the synchronization likelihood correlated with global cognitive status as measured by the Mini Mental State Evaluation. The present results suggest that at group level, fronto-parietal coupling of the delta and alpha rhythms progressively becomes abnormal though MCI and mild AD. Future longitudinal research should evaluate whether the present EEG approach is able to predict the cognitive decline in individual MCI subjects.

Alpha rhythms in mild dements during visual delayed choice reaction time tasks: A MEG study

Can simple delayed response tasks affect latency and amplitude of magnetoencephalographic midline alpha rhythms (6-12 Hz) in early dementia? We recruited 15 mild Alzheimer's disease (AD) and 10 vascular dementia (VaD) patients (paired mini mental state exam of 17-24). The control groups comprised 18 young and 22 elderly normal subjects. In the first task, a simple "cue" stimulus (one bit) was memorized along a brief delay period (3.5-5.5s) up to a "go" stimulus triggering (right or left) button press. In the second task, the "cue" stimulus remained available along the delay period. Event-related reduction in power of the alpha rhythms indexed the cortical activation (event-related desynchronization, ERD) for the trials associated with correct behavioral responses. Behavioral performances to both tasks were lower in the AD and VaD patients than in the normal subjects. In particular, just four AD and five VaD patients executed a sufficient amount of correct responses for the alpha ERD analysis, so they were included in a unique group. In both tasks, the alpha ERD peak was later in latency in the demented and normal elderly subjects than in the normal young subjects. Furthermore, the alpha ERD peak was stronger in amplitude in the demented patients than in the normal subjects. These results suggest that simple delayed response tasks during physiological recordings are quite difficult for patients even at an early dementia stage. Such difficulty may induce the abnormal amount of the related cortical activation in dementia as revealed by the alpha ERD.

Electroencephalogram in the dementia workup

Dementia is affecting an increasing proportion of the population in the developed world. It is important to reach a correct diagnosis of dementia, because this has implications on the treatment. The electroencephalogram (EEG) is, in general, not a sensitive test for detecting dementia and is not recommended in the standard workup of dementia. In spite of this, however, EEG is useful in patients with deteriorating mental status in whom dementia is suspected mainly to rule out delirium, depression, atypical complex partial seizures, and prion disease. An EEG also provides insight into the physiology of different dementia types. The EEG is most useful when interpreted within a well-defined clinical context, such as knowing the patient's degree of cognitive impairment. It is a noninvasive and inexpensive test, and the threshold should be low for ordering it. This article summarizes EEG findings with aging, different dementia types, and conditions masked as dementia.

Early Event-Related Potential Changes During Working Memory Activation Predict Rapid Decline in Mild Cognitive Impairment

BACKGROUND

The conversion of mild cognitive impairment (MCI) to Alzheimer's disease is associated with substantial compromise of neocortical circuits subserving rapid cognitive functions such as working memory. Event-related potential (ERP) analysis is a powerful tool to identify early impairment of these circuits, yet research for an electrophysiological marker of cognitive deterioration in MCI is scarce. Using a "2-back" activation paradigm, we recently described an electrophysiological correlate of working memory activation (positive-negative working memory [PN(wm)] component) over parietal electrodes.

METHODS

Ours was a longitudinal study of 24 MCI patients with ERP analysis at inclusion and neuropsychological follow-up after 1 year. We used ERP waveform subtraction analysis between the n-back and control tasks. Analysis of variance (ANOVA) was used to compare electroencephalograph latencies between progressive MCI (PMCI) and stable MCI (SMCI), and univariate regression was used to assess the relationship between neuropsychological measures at baseline and clinical outcome.

RESULTS

Thirteen (54%) MCI patients showed PMCI, and 11 (46%) remained stable (SMCI). In SMCI, a PN(wm) component with significantly larger density compared to baseline was identified when subtracting the detection task for both the 1- and 2-back tasks. In contrast, in PMCI, the PN(wm) component was absent in both 1-back and 2-back conditions. Neuropsychological variables and n-back test performance at inclusion did not predict cognitive deterioration 1 year later.

CONCLUSIONS

In conjunction with recent functional imaging data, the present results support the notion of an early dysfunction of neural generators within the parietal cortex in MCI. They also reveal that the absence of the PN(wm) component may provide an easily applicable qualitative predictive marker of rapid cognitive deterioration in MCI.

EEG dynamics in patients with Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disorder characterized by cognitive and intellectual deficits and behavior disturbance. The electroencephalogram (EEG) has been used as a tool for diagnosing AD for several decades. The hallmark of EEG abnormalities in AD patients is a shift of the power spectrum to lower frequencies and a decrease in coherence of fast rhythms. These abnormalities are thought to be associated with functional disconnections among cortical areas resulting from death of cortical neurons, axonal pathology, cholinergic deficits, etc. This article reviews main findings of EEG abnormalities in AD patients obtained from conventional spectral analysis and nonlinear dynamical methods. In particular, nonlinear alterations in the EEG of AD patients, i.e. a decreased complexity of EEG patterns and reduced information transmission among cortical areas, and their clinical implications are discussed. For future studies, improvement of the accuracy of differential diagnosis and early detection of AD based on multimodal approaches, longitudinal studies on nonlinear dynamics of the EEG, drug effects on the EEG dynamics, and linear and nonlinear functional connectivity among cortical regions in AD are proposed to be investigated. EEG abnormalities of AD patients are characterized by slowed mean frequency, less complex activity, and reduced coherences among cortical regions. These abnormalities suggest that the EEG has utility as a valuable tool for differential and early diagnosis of AD.

A critical discussion of the role of neuroimaging in mild cognitive impairment

OBJECTIVE

In this paper, the current neuroimaging literature is reviewed with regard to characteristic findings in mild cognitive impairment (MCI). Particular attention is drawn to the possible value of neuroimaging modalities in the prediction and early diagnosis of Alzheimer's disease (AD).

METHODS

First, the potential contribution of neuroimaging to an early, preclinical diagnosis of degenerative disorders is discussed at the background of our knowledge about the pathogenesis of AD. Second, relevant neuroimaging studies focusing on MCI are explored and summarized. Neuroimaging studies were found through Medline search and by systematically checking through the bibliographies of relevant articles.

RESULTS

Structural volumetric magnetic resonance imaging (MRI) and positron emission tomography (PET)/single photon emission tomography (SPECT) are currently the most commonly used neuroimaging modalities in studies focusing on MCI. There were considerable variations in demographical and clinical characteristics across studies. However, significant hippocampal and entorhinal cortex volume reductions were consistently found in subjects with MCI as compared with cognitively unimpaired controls. While hippocampal and entorhinal cortex atrophy in subjects with MCI are also well-established risk factors for the development of AD, these measures cannot be regarded as being of high predictive value in an individual case. Evidence for other typical neuroimaging changes in MCI is still scarce. In PET and SPECT studies, reduced blood flow and/or glucose metabolism in temporoparietal association areas, posterior cingulate and hippocampus were associated with a higher risk of progressive cognitive decline in MCI. In quantitative electroencephalogram (QEEG), low beta, high theta, low alpha and slowed mean frequency were associated with development of dementia.

CONCLUSIONS

Existing studies suggest that neuroimaging measures have the potential to become valuable tools in the early diagnosis of AD. To establish their value in routine use, larger studies, preferably with long prospective follow-up are needed.