Decreased Parietal Beta Power as a Sign of Disease Progression in Patients with Mild Cognitive Impairment

Quantitative electroencephalography (qEEG), apolipoprotein A-I (APOA-I), and apolipoprotein epsilon 4 (APOE ɛ4) alleles for the diagnosis of mild cognitive impairment and Alzheimer's disease

INTRODUCTION

Alzheimer's disease (AD) is the most common type of dementia. Amnestic mild cognitive impairment (aMCI), a pre-dementia stage is an important stage for early diagnosis and intervention. This study aimed to investigate the diagnostic value of qEEG, APOA-I, and APOE ɛ4 allele in aMCI and AD patients and found the correlation between qEEG (Delta + Theta)/(Alpha + Beta) ratio (DTABR) and different cognitive domains.

METHODS

All participants were divided into three groups: normal controls (NCs), aMCI, and AD, and all received quantitative electroencephalography (qEEG), neuropsychological scale assessment, apolipoprotein epsilon 4 (APOE ɛ4) alleles, and various blood lipid indicators. Different statistical methods were used for different data.

RESULTS

The cognitive domains except executive ability were all negatively correlated with DTABR in different brain regions while executive ability was positively correlated with DTABR in several brain regions, although without statistical significance. The consequences confirmed that the DTABR of each brain area were related to MMSE, MoCA, instantaneous memory, and the language ability (p < 0.05), and the DTABR in the occipital area was relevant to all cognitive domains (p < 0.01) except executive function (p = 0.272). Also, occipital DTABR was most correlated with language domain when tested by VFT with a moderate level (r = 0.596, p < 0.001). There were significant differences in T3, T5, and P3 DTABR between both AD and NC and aMCI and NCs. As for aMCI diagnosis, the maximum AUC was achieved when using T3 combined with APOA-I and APOE ε4 (0.855) and the maximum AUC was achieved when using T5 combined with APOA-I and APOE ε4 (0.889) for AD diagnosis.

CONCLUSION

These findings highlight that APOA-I, APOE ɛ4, and qEEG play an important role in aMCI and AD diagnosis. During AD continuum, qEEG DTABR should be taken into consideration for the early detection of AD risk.

The fusion of multi-omics profile and multimodal EEG data contributes to the personalized diagnostic strategy for neurocognitive disorders

BACKGROUND

The increasing prevalence of neurocognitive disorders (NCDs) in the aging population worldwide has become a significant concern due to subjectivity of evaluations and the lack of precise diagnostic methods and specific indicators. Developing personalized diagnostic strategies for NCDs has therefore become a priority.

RESULTS

Multimodal electroencephalography (EEG) data of a matched cohort of normal aging (NA) and NCDs seniors were recorded, and their faecal samples and urine exosomes were collected to identify multi-omics signatures and metabolic pathways in NCDs by integrating metagenomics, proteomics, and metabolomics analysis. Additionally, experimental verification of multi-omics signatures was carried out in aged mice using faecal microbiota transplantation (FMT). We found that NCDs seniors had low EEG power spectral density and identified specific microbiota, including Ruminococcus gnavus, Enterocloster bolteae, Lachnoclostridium sp. YL 32, and metabolites, including L-tryptophan, L-glutamic acid, gamma-aminobutyric acid (GABA), and fatty acid esters of hydroxy fatty acids (FAHFAs), as well as disturbed biosynthesis of aromatic amino acids and TCA cycle dysfunction, validated in aged mice. Finally, we employed a support vector machine (SVM) algorithm to construct a machine learning model to classify NA and NCDs groups based on the fusion of EEG data and multi-omics profiles and the model demonstrated 92.69% accuracy in classifying NA and NCDs groups.

CONCLUSIONS

Our study highlights the potential of multi-omics profiling and EEG data fusion in personalized diagnosis of NCDs, with the potential to improve diagnostic precision and provide insights into the underlying mechanisms of NCDs. Video Abstract.

Effectiveness of an enhanced simultaneous cognitive-physical dual-task training based on fairy tales (ESCARF) in older adults with mild cognitive impairment

The aim of this study was to provide a dual-task program that included cognitive and physical training to older adults with mild cognitive impairment (MCI) and evaluate its effects. A single-group pretest-posttest design was performed using 15 older adults with MCI. A 12-week enhanced simultaneous cognitive-physical dual-task training based on fairy tales (ESCARF) program was conducted from September 2019 to December 2019. Participants were assessed using the Korean version of the Montreal Cognitive Assessment, electroencephalography (EEG), muscle strength, flexibility, agility, memory self-efficacy questionnaire, physical self-efficacy scale, and quality of life before and after 6 and 12 weeks of the intervention. The ESCARF program significantly improved cognitive function, physical function, self-efficacy, and quality of life in older adults with MCI. These findings will provide insights into the development and implementation of customized cognitive interventions to prevent or delay the onset of cognitive decline in older adults with MCI.

A holo-spectral EEG analysis provides an early detection of cognitive decline and predicts the progression to Alzheimer's disease

Aims

Our aim was to differentiate patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from cognitively normal (CN) individuals and predict the progression from MCI to AD within a 3-year longitudinal follow-up. A newly developed Holo-Hilbert Spectral Analysis (HHSA) was applied to resting state EEG (rsEEG), and features were extracted and subjected to machine learning algorithms.

Methods

A total of 205 participants were recruited from three hospitals, with CN (n = 51, MMSE > 26), MCI (n = 42, CDR = 0.5, MMSE ≥ 25), AD1 (n = 61, CDR = 1, MMSE < 25), AD2 (n = 35, CDR = 2, MMSE < 16), and AD3 (n = 16, CDR = 3, MMSE < 16). rsEEG was also acquired from all subjects. Seventy-two MCI patients (CDR = 0.5) were longitudinally followed up with two rsEEG recordings within 3 years and further subdivided into an MCI-stable group (MCI-S, n = 36) and an MCI-converted group (MCI-C, n = 36). The HHSA was then applied to the rsEEG data, and features were extracted and subjected to machine-learning algorithms.

Results

(a) At the group level analysis, the HHSA contrast of MCI and different stages of AD showed augmented amplitude modulation (AM) power of lower-frequency oscillations (LFO; delta and theta bands) with attenuated AM power of higher-frequency oscillations (HFO; beta and gamma bands) compared with cognitively normal elderly controls. The alpha frequency oscillation showed augmented AM power across MCI to AD1 with a reverse trend at AD2. (b) At the individual level of cross-sectional analysis, implementation of machine learning algorithms discriminated between groups with good sensitivity (Sen) and specificity (Spec) as follows: CN elderly vs. MCI: 0.82 (Sen)/0.80 (Spec), CN vs. AD1: 0.94 (Sen)/0.80 (Spec), CN vs. AD2: 0.93 (Sen)/0.90 (Spec), and CN vs. AD3: 0.75 (Sen)/1.00 (Spec). (c) In the longitudinal MCI follow-up, the initial contrasted HHSA between MCI-S and MCI-C groups showed significantly attenuated AM power of alpha and beta band oscillations. (d) At the individual level analysis of longitudinal MCI groups, deploying machine learning algorithms with the best seven features resulted in a sensitivity of 0.9 by the support vector machine (SVM) classifier, with a specificity of 0.8 yielded by the decision tree classifier.

Conclusion

Integrating HHSA into EEG signals and machine learning algorithms can differentiate between CN and MCI as well as also predict AD progression at the MCI stage.

Paroxysmal Slow-Wave Events Are Uncommon in Parkinson's Disease

Background: Parkinson’s disease (PD) is currently considered to be a multisystem neurodegenerative disease that involves cognitive alterations. EEG slowing has been associated with cognitive decline in various neurological diseases, such as PD, Alzheimer’s disease (AD), and epilepsy, indicating cortical involvement. A novel method revealed that this EEG slowing is composed of paroxysmal slow-wave events (PSWE) in AD and epilepsy, but in PD it has not been tested yet. Therefore, this study aimed to examine the presence of PSWE in PD as a biomarker for cortical involvement. Methods: 31 PD patients, 28 healthy controls, and 18 juvenile myoclonic epilepsy (JME) patients (served as positive control), underwent four minutes of resting-state EEG. Spectral analyses were performed to identify PSWEs in nine brain regions. Mixed-model analysis was used to compare between groups and brain regions. The correlation between PSWEs and PD duration was examined using Spearman’s test. Results: No significant differences in the number of PSWEs were observed between PD patients and controls (p > 0.478) in all brain regions. In contrast, JME patients showed a higher number of PSWEs than healthy controls in specific brain regions (p < 0.023). Specifically in the PD group, we found that a higher number of PSWEs correlated with longer disease duration. Conclusions: This study is the first to examine the temporal characteristics of EEG slowing in PD by measuring the occurrence of PSWEs. Our findings indicate that PD patients who are cognitively intact do not have electrographic manifestations of cortical involvement. However, the correlation between PSWEs and disease duration may support future studies of repeated EEG recordings along the disease course to detect early signs of cortical involvement in PD.

Effect of Electrical Muscle Stimulation and Resistance Exercise Intervention on Physical and Brain Function in Middle-Aged and Older Women

This study investigated the effectiveness of electrical muscle stimulation (EMS) with resistance exercise training (ERT) and resistance exercise training (RT) on physical and brain function in middle-aged and older women. Method: Forty-eight participants were randomly allocated into three groups: (i) ERT (n = 16), (ii) RT (n = 16), and (iii) control group (n = 16). The intervention session was 50 min long and performed three times/week for four weeks. The ERT group performed quadriceps setting, straight leg raises, and ankle pump exercises while constantly receiving EMS on their quadriceps muscle on both legs. The RT group performed the same exercise without EMS. Physical function was measured using skeletal muscle mass index (SMI), handgrip strength, gait speed, five times sit-to-stand test (FTSS) and timed up-and-go test (TUG). Brain function was assessed with electroencephalogram measurement of whole brain activity. Results: After four-week intervention, significant improvements were observed in SMI (p < 0.01), phase angle (p < 0.05), and gait speed (p < 0.05) in the ERT group compared to the control group. ERT also increased muscle strength (p < 0.05) and mobility in lower limbs as observed in FTSS and TUG tests (p < 0.05) at post-intervention compared to the baseline. In the ERT group, significant positive changes were observed in Beta1 band power, Theta band power, and Alpha1 band whole brain connectivity (p < 0.005) compared to the control group. Conclusions: Our findings showed that ERT can improve muscle and brain function in middle-aged and older adults during a four-week intervention program whereas significant improvements were not observed with RT. Therefore might be one of the feasible alternative intervention to RT for the prevention of muscle loss whilst improving brain function for middle-aged and older population.

Virtual Reality and Exercise Training Enhance Brain, Cognitive, and Physical Health in Older Adults with Mild Cognitive Impairment

We investigated the effectiveness of virtual-reality-based cognitive training (VRCT) and exercise on the brain, cognitive, physical and activity of older adults with mild cognitive impairment (MCI).

METHODS

This study included 99 participants (70.8 ± 5.4) with MCI in the VRCT, exercise, and control groups. The VRCT consisted of a series of games targeting different brain functions such as executive function, memory, and attention. Twenty-four sessions of VRCT (three days/week) were performed, and each session was 100 min long. Exercise intervention consisted of aerobic and resistance trainings performed in 24 sessions for 60 min (2 times/week for 12 weeks). Global cognitive function was measured using the Mini-Mental State Examination (MMSE) test. Resting-state electroencephalography (EEG) of the neural oscillatory activity in different frequency bands was performed. Physical function was measured using handgrip strength (HGS) and gait speed.

RESULTS

After the intervention period, VRCT significantly improved the MMSE scores (p < 0.05), and the exercise group had significantly improved HGS and MMSE scores (p < 0.05) compared to baseline. One-way analysis of variance (ANOVA) of resting-state EEG showed a decreased theta/beta power ratio (TBR) (p < 0.05) in the central region of the brain in the exercise group compared to the control group. Although not statistically significant, the VRCT group also showed a decreased TBR compared to the control group. The analysis of covariance (ANCOVA) test showed a significant decrease in theta band power in the VRCT group compared to the exercise group and a decrease in delta/alpha ratio in the exercise group compared to the VRCT group.

CONCLUSION

Our findings suggest that VRCT and exercise training enhances brain, cognitive, and physical health in older adults with MCI. Further studies with a larger population sample to identify the effect of VRCT in combination with exercise training are required to yield peak benefits for patients with MCI.

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].

Effects of the Duration of a Resting-State EEG Recording in Healthy Aging and Mild Cognitive Impairment

INTRODUCTION

The recording of resting-state EEG may provide a means to predict early cognitive decline associated with mild cognitive impairment (MCI). Previous studies have typically used very short recording times to avoid a confound with drowsiness that may occur in longer recordings. The effects of a longer recording have not however been systematically examined.

METHODS

Eyes-closed resting-state EEG activity was recorded in 40 older adult participants (20 healthy older adults and 20 people with MCI). The recording period was a relatively long 6 minutes, divided into two equal 3-minute halves to determine if drowsiness will be more apparent as the recording progresses. The participants also completed standardized neuropsychological tasks that assessed global cognition (Montreal Cognitive Assessment) and memory (California Verbal Learning Test, Second Edition). A spectral analysis was performed on both short (2 seconds) and long (8 seconds) segments in both 3-minute halves.

RESULTS

No differences in power density for any of the EEG frequency bands were found between the 2 halves of the study for either group. There was little evidence of increased drowsiness in the second half of the study even when frequency resolution was increased with the 8-second segmentation. Theta power density was overall larger for people with MCI compared to healthy older adults. A negative correlation was also observed between theta power and global cognition in healthy older adults.

CONCLUSIONS

The present results indicate that longer resting-state EEG recording can be reliably employed without increased risk of drowsiness.

Resting state electroencephalographic rhythms are affected by immediately preceding memory demands in cognitively unimpaired elderly and patients with mild cognitive impairment

Experiments on event-related electroencephalographic oscillations in aged people typically include blocks of cognitive tasks with a few minutes of interval between them. The present exploratory study tested the effect of being engaged on cognitive tasks over the resting state cortical arousal after task completion, and whether it differs according to the level of the participant’s cognitive decline. To investigate this issue, we used a local database including data in 30 healthy cognitively unimpaired (CU) persons and 40 matched patients with amnestic mild cognitive impairment (aMCI). They had been involved in 2 memory tasks for about 40 min and underwent resting-state electroencephalographic (rsEEG) recording after 5 min from the task end. eLORETA freeware estimated rsEEG alpha source activity as an index of general cortical arousal. In the CU but not aMCI group, there was a negative correlation between memory tasks performance and posterior rsEEG alpha source activity. The better the memory tasks performance, the lower the posterior alpha activity (i.e., higher cortical arousal). There was also a negative correlation between neuropsychological test scores of global cognitive status and alpha source activity. These results suggest that engagement in memory tasks may perturb background brain arousal for more than 5 min after the tasks end, and that this effect are dependent on participants global cognitive status. Future studies in CU and aMCI groups may cross-validate and extend these results with experiments including (1) rsEEG recordings before memory tasks and (2) post-tasks rsEEG recordings after 5, 15, and 30 min.

Quantitative electroencephalography changes in patients with mild cognitive impairment after choline alphoscerate administration

There is limited evidence on the effectiveness of choline alphoscerate for mild cognitive impairment (MCI) in studies using neuropsychological markers. The aim of this study was to evaluate the spectral change at a source level using quantitative electroencephalography (qEEG) as a biomarker for cognitive function after choline alphoscerate administration to patients with MCI. This study used the qEEG data of patients with MCI who visited the Department of Neurology of the Chung-Ang University Hospital between April 2017 and December 2018. Resting-state EEG studies were performed on 33 patients with MCI at baseline and compared with those of the 18 normal controls selected from the community. After baseline qEEG, choline alphoscerate 400 mg was administered twice daily for 2 months to the patients with MCI. Follow-up qEEG was performed in 20 subjects. Baseline qEEG of patients with MCI was compared to qEEG after choline alphoscerate administration. We found that the MCI group exhibited a decreased alpha power compared to that of the control group. Patients with MCI treated with choline alphoscerate exhibited a decrease in the theta and delta power of the parietal and temporal lobe and an increase in the alpha power spectrum of the occipital lobes. We also identified the trend of default mode network enhancement after choline alphoscerate administration. Our results suggest that choline alphoscerate may have a positive effect in patients with MCI and support the usefulness of qEEG for monitoring the therapeutic effect of nootropics.

Perioperative Electroencephalogram Spectral Dynamics Related to Postoperative Delirium in Older Patients

BACKGROUND

Intraoperative electroencephalography (EEG) signatures related to the development of postoperative delirium (POD) in older patients are frequently studied. However, a broad analysis of the EEG dynamics including preoperative, postinduction, intraoperative and postoperative scenarios and its correlation to POD development is still lacking. We explored the relationship between perioperative EEG spectra-derived parameters and POD development, aiming to ascertain the diagnostic utility of these parameters to detect patients developing POD.

METHODS

Patients aged ≥65 years undergoing elective surgeries that were expected to last more than 60 minutes were included in this prospective, observational single center study (Biomarker Development for Postoperative Cognitive Impairment [BioCog] study). Frontal EEGs were recorded, starting before induction of anesthesia and lasting until recovery of consciousness. EEG data were analyzed based on raw EEG files and downloaded excel data files. We performed multitaper spectral analyses of relevant EEG epochs and further used multitaper spectral estimate to calculate a corresponding spectral parameter. POD assessments were performed twice daily up to the seventh postoperative day. Our primary aim was to analyze the relation between the perioperative spectral edge frequency (SEF) and the development of POD.

RESULTS

Of the 237 included patients, 41 (17%) patients developed POD. The preoperative EEG in POD patients was associated with lower values in both SEF (POD 13.1 ± 4.6 Hz versus no postoperative delirium [NoPOD] 17.4 ± 6.9 Hz; P = .002) and corresponding γ-band power (POD -24.33 ± 2.8 dB versus NoPOD -17.9 ± 4.81 dB), as well as reduced postinduction absolute α-band power (POD -7.37 ± 4.52 dB versus NoPOD -5 ± 5.03 dB). The ratio of SEF from the preoperative to postinduction state (SEF ratio) was ~1 in POD patients, whereas NoPOD patients showed a SEF ratio >1, thus indicating a slowing of EEG with loss of unconscious. Preoperative SEF, preoperative γ-band power, and SEF ratio were independently associated with POD (P = .025; odds ratio [OR] = 0.892, 95% confidence interval [CI], 0.808-0.986; P = .029; OR = 0.568, 95% CI, 0.342-0.944; and P = .009; OR = 0.108, 95% CI, 0.021-0.568, respectively).

CONCLUSIONS

Lower preoperative SEF, absence of slowing in EEG while transitioning from preoperative state to unconscious state, and lower EEG power in relevant frequency bands in both these states are related to POD development. These findings may suggest an underlying pathophysiology and might be used as EEG-based marker for early identification of patients at risk to develop POD.

Functional Connectivity Alterations Based on the Weighted Phase Lag Index: An Exploratory Electroencephalography Study on Alzheimer's Disease

OBJECTIVE

Numerous electroencephalography (EEG) studies focus on the alteration of electrical activity in patients with Alzheimer's Disease (AD), but there are no consistent results especially regarding functional connectivity. We supposed that the weighted Phase Lag Index (w- PLI), as phase-based measures of functional connectivity, may be used as an auxiliary diagnostic method for AD.

METHODS

We enrolled 30 patients with AD, 30 patients with Mild Cognitive Impairment (MCI), and 30 Healthy Controls (HC). EEGs were recorded in all participants at baseline during relaxed wakefulness. Following EEG preprocessing, Power Spectral Density (PSD) and wPLI parameters were determined to further analyze whether they were correlated to cognitive scores.

RESULTS

In the patients with AD, the increased PSD in theta band was presented compared with MCI and HC groups, which was associated with disturbances of the directional, computational, and delayed memory capacity. Furthermore, the wPLI revealed a distinctly lower connection strength between frontal and distant areas in the delta band and a higher connection strength of the central and temporo-occipital region in the theta band for AD patients. Moreover,we found a significant negative correlation between theta functional connectivity and cognitive scores.

CONCLUSION

Increased theta PSD and decreased delta wPLI may be one of the earliest changes in AD and associated with disease severity. The parameter wPLI is a novel measurement of phase synchronization and has potentials in understanding underlying functional connectivity and aiding in the diagnostics of AD.

Simultaneous cognitive-physical dual task training based on fairy tales in older adults with mild cognitive impairment: A pilot study

In this study, we aimed to develop a simultaneous cognitive-physical dual-task training program based on familiar cultural backgrounds using fairy tales and to explore its feasibility and preliminary effects, including effects on neurophysiological, cognitive, and physical functions. A single-group pretest-posttest design (n = 9) was employed to evaluate the effects of the cognitive-physical intervention performed for 60-90 min once a week for 12 weeks. The findings showed that perceived memory and physical self-efficacy, muscle strength, and cognitive function were significantly increased after the intervention. Although the relative beta band power measured using electroencephalography showed a tendency to increase in eight brain domains after the 12-week intervention, the changes were not significant. Findings suggested that the intervention was feasible and provided beneficial effects on cognitive and physical functions in older adults with mild cognitive impairment. Future research on larger sample sizes using randomized controlled trials is needed to determine the effectiveness of such interventions on neurophysiological functions.

Feasibility of Repeated Assessment of Cognitive Function in Older Adults Using a Wireless, Mobile, Dry-EEG Headset and Tablet-Based Games

Access to affordable, objective and scalable biomarkers of brain function is needed to transform the healthcare burden of neuropsychiatric and neurodegenerative disease. Electroencephalography (EEG) recordings, both resting and in combination with targeted cognitive tasks, have demonstrated utility in tracking disease state and therapy response in a range of conditions from schizophrenia to Alzheimer's disease. But conventional methods of recording this data involve burdensome clinic visits, and behavioural tasks that are not effective in frequent repeated use. This paper aims to evaluate the technical and human-factors feasibility of gathering large-scale EEG using novel technology in the home environment with healthy adult users. In a large field study, 89 healthy adults aged 40-79 years volunteered to use the system at home for 12 weeks, 5 times/week, for 30 min/session. A 16-channel, dry-sensor, portable wireless headset recorded EEG while users played gamified cognitive and passive tasks through a tablet application, including tests of decision making, executive function and memory. Data was uploaded to cloud servers and remotely monitored via web-based dashboards. Seventy-eight participants completed the study, and high levels of adherence were maintained throughout across all age groups, with mean compliance over the 12-week period of 82% (4.1 sessions per week). Reported ease of use was also high with mean System Usability Scale scores of 78.7. Behavioural response measures (reaction time and accuracy) and EEG components elicited by gamified stimuli (P300, ERN, Pe and changes in power spectral density) were extracted from the data collected in home, across a wide range of ages, including older adult participants. Findings replicated well-known patterns of age-related change and demonstrated the feasibility of using low-burden, large-scale, longitudinal EEG measurement in community-based cohorts. This technology enables clinically relevant data to be recorded outside the lab/clinic, from which metrics underlying cognitive ageing could be extracted, opening the door to potential new ways of developing digital cognitive biomarkers for disorders affecting the brain.

Differences between memory encoding and retrieval failure in mild cognitive impairment: results from quantitative electroencephalography and magnetic resonance volumetry

BACKGROUND

The memory impairments in mild cognitive impairment (MCI) can be classified into encoding (EF) and retrieval (RF) failure, which can be affected by underlying pathomechanism. We explored the differences structurally and functionally.

METHODS

We compared quantitative electroencephalography (qEEG) power spectra and connectivity between 87 MCI patients with EF and 78 MCI with RF using iSyncBrain® (iMediSync Inc., Republic of Korea) ( https://isyncbrain.com/ ). Voxel-based morphometric analysis of the gray matter (GM) in the MCI groups and 71 cognitive normal controls was also done using the Computational Anatomy Toolbox 12 ( http://www.neuro.uni-jena.de/cat/ ).

RESULTS

qEEG showed higher frontal theta and lower beta2 band power, and higher theta connectivity in the EF. There was no statistically significant difference in GM volume between the EF and RF. However, when compared to normal control, GM volume reductions due to EF in the left thalamus and bilateral hippocampi and reductions due to RF in the left thalamus, right superior frontal lobe, right superior temporal lobe, and right middle cingulum were observed (p < 0.05, family-wise error correction).

CONCLUSIONS

MCI differs functionally and structurally according to their specific memory impairments. The EF findings are structurally and functionally more consistent with the prodromal Alzheimer's disease stage than the RF findings. Since this study is a cross-sectional study, prospective follow-up studies are needed to investigate whether different types of memory impairments can predict the underlying pathology of amnestic MCI. Additionally, insufficient sample size may lead to ambiguous statistical findings in direct comparisons, and a larger patient cohort could more robustly identify differences in GM volume reductions between the EF and the RF group.

Olfactory response as a marker for Alzheimer's disease: Evidence from perceptual and frontal lobe oscillation coherence deficit

High-frequency oscillations of the frontal cortex are involved in functions of the brain that fuse processed data from different sensory modules or bind them with elements stored in the memory. These oscillations also provide inhibitory connections to neural circuits that perform lower-level processes. Deficit in the performance of these oscillations has been examined as a marker for Alzheimer's disease (AD). Additionally, the neurodegenerative processes associated with AD, such as the deposition of amyloid-beta plaques, do not occur in a spatially homogeneous fashion and progress more prominently in the medial temporal lobe in the early stages of the disease. This region of the brain contains neural circuitry involved in olfactory perception. Several studies have suggested that olfactory deficit can be used as a marker for early diagnosis of AD. A quantitative assessment of the performance of the olfactory system can hence serve as a potential biomarker for Alzheimer's disease, offering a relatively convenient and inexpensive diagnosis method. This study examines the decline in the perception of olfactory stimuli and the deficit in the performance of high-frequency frontal oscillations in response to olfactory stimulation as markers for AD. Two measurement modalities are employed for assessing the olfactory performance: 1) An interactive smell identification test is used to sample the response to a sizable variety of odorants, and 2) Electroencephalography data are collected in an olfactory perception task with a pair of selected odorants in order to assess the connectivity of frontal cortex regions. Statistical analysis methods are used to assess the significance of selected features extracted from the recorded modalities as Alzheimer's biomarkers. Olfactory decline regressed to age in both healthy and mild AD groups are evaluated, and single- and multi-modal classifiers are also developed. The novel aspects of this study include: 1) Combining EEG response to olfactory stimulation with behavioral assessment of olfactory perception as a marker of AD, 2) Identification of odorants most significantly affected in mild AD patients, 3) Identification of odorants which are still adequately perceived by mild AD patients, 4) Analysis of the decline in the spatial coherence of different oscillatory bands in response to olfactory stimulation, and 5) Being the first study to quantitatively assess the performance of olfactory decline due to aging and AD in the Iranian population.

Alpha Power and Functional Connectivity in Cognitive Decline: A Systematic Review and Meta-Analysis

Background:

Mild cognitive impairment (MCI) is a stage between expected age-related cognitive decline and dementia. Dementias have been associated with changes in neural oscillations across the frequency spectrum, including the alpha range. Alpha is the most prominent rhythm in human EEG and is best detected during awake resting state (RS). Though several studies measured alpha power and synchronization in MCI, findings have not yet been integrated.

Objective:

To consolidate findings on power and synchronization of alpha oscillations across stages of cognitive decline.

Methods:

We included studies published until January 2020 that compared power or functional connectivity between 1) people with MCI and cognitively healthy older adults (OA) or people with a neurodegenerative dementia, and 2) people with progressive and stable MCI. Random-effects meta-analyses were performed when enough data was available.

Results:

Sixty-eight studies were included in the review. Global RS alpha power was lower in AD than in MCI (ES = –0.30; 95% CI = –0.51, –0.10; k = 6), and in MCI than in OA (ES = –1.49; 95% CI = –2.69, –0.29; k = 5). However, the latter meta-analysis should be interpreted cautiously due to high heterogeneity. The review showed lower RS alpha power in progressive than in stable MCI, and lower task-related alpha reactivity in MCI than in OA. People with MCI had both lower and higher functional connectivity than OA. Publications lacked consistency in MCI diagnosis and EEG measures.

Conclusion:

Research indicates that RS alpha power decreases with increasing impairment, and could—combined with measures from other frequency bands—become a biomarker of early cognitive decline.

Altered Low-Frequency EEG Connectivity in Mild Cognitive Impairment as a Sign of Clinical Progression

BACKGROUND

Mild cognitive impairment (MCI) is associated with clinical progression to Alzheimer's disease (AD) but not all patients with MCI convert to AD. However, it is important to have methods that can differentiate between patients with MCI who progress (pMCI) and those who remain stable (sMCI), i.e., for timely administration of disease-modifying drugs.

OBJECTIVE

In the current study, we wanted to investigate whether quantitative EEG coherence and imaginary part of coherency (iCoh) could be used to differentiate between pMCI and sMCI.

METHODS

17 patients with AD, 27 patients with MCI, and 38 older healthy controls were recruited and followed for three years and 2nd year was used to determine progression. EEGs were recorded at baseline and coherence and iCoh were calculated after thorough preprocessing.

RESULTS

Between pMCI and sMCI, the largest difference in total coherence was found in the theta and delta bands. Here, the significant differences for coherence and iCoh were found in the lower frequency bands involving the temporal-frontal connections for coherence and parietal-frontal connections for iCoh. Furthermore, we found a significant negative correlation between theta coherence and the Addenbrooke's Cognitive Examination (ACE) (p = 0.0378; rho = -0.2388).

CONCLUSION

These findings suggest that low frequency coherence and iCoh can be used to determine, which patients with MCI will progress to AD and is associated with the ACE score. Low-frequency coherence has previously been associated with increased hippocampal atrophy and degeneration of the cholinergic system and may be an early marker of AD pathology.

Electroencephalographic Cross-Frequency Coupling as a Sign of Disease Progression in Patients With Mild Cognitive Impairment: A Pilot Study

Mild cognitive impairment (MCI) refers to mild objective cognitive deficits and is associated with the later development of Alzheimer’s disease (AD). However, not all patients with MCI convert to AD. EEG spectral power has shown promise as a marker of progression, but brain oscillations in different frequencies are not isolated entities. Coupling between different frequency bands, so-called cross-frequency coupling (CFC), has been associated with memory function and may further contribute to our understanding of what characterizes patients with MCI who progress to AD. In the current study, we wanted to investigate the changes in gamma/theta CFC in patients with AD and MCI compared to HC and in patients with pMCI compared to patients with sMCI. Furthermore, we wanted to investigate the association with cognitive test scores. EEGs were included at baseline for 15 patients with AD, 25 patients with MCI, and 36 older HC, and the participants were followed for up to 3 years. To investigate CFC, we calculated the modulation index (MI), which has been shown to be less affected by noisy data compared to other techniques. We found that patients with pMCI showed a significantly lower global gamma/theta CFC compared to patients with sMCI. In addition, global gamma/theta CFC was significantly correlated with Addenbrooke’s Cognitive Examination (ACE) score (p-value = 0.030, rho = 0.527). Although not significant, patients with AD and MCI showed a lower gamma/theta CFC compared to HC. These findings suggest that gamma/theta CFC is important for proper cognitive functioning and that a decrease in gamma/theta CFC in patients with MCI may be a sign of progression. Gamma/theta CFC may therefore serve as a progression marker in MCI, but larger studies are needed to validate these findings.

Changes in the left temporal microstate are a sign of cognitive decline in patients with Alzheimer's disease

INTRODUCTION

Large-scale brain networks are disrupted in the early stages of Alzheimer's disease (AD). Electroencephalography microstate analysis, a promising method for studying brain networks, parses EEG signals into topographies representing discrete, sequential network activations. Prior studies indicate that patients with AD show a pattern of global microstate disorganization. We investigated whether any specific microstate changes could be found in patients with AD and mild cognitive impairment (MCI) compared to healthy controls (HC).

MATERIALS AND METHODS

Standard EEGs were obtained from 135 HC, 117 patients with MCI, and 117 patients with AD from six Nordic memory clinics. We parsed the data into four archetypal microstates.

RESULTS

There was significantly increased duration, occurrence, and coverage of microstate A in patients with AD and MCI compared to HC. When looking at microstates in specific frequency bands, we found that microstate A was affected in delta (1-4 Hz), theta (4-8 Hz), and beta (13-30 Hz), while microstate D was affected only in the delta and theta bands. Microstate features were able to separate HC from AD with an accuracy of 69.8% and HC from MCI with an accuracy of 58.7%.

CONCLUSIONS

Further studies are needed to evaluate whether microstates represent a valuable disease classifier. Overall, patients with AD and MCI, as compared to HC, show specific microstate alterations, which are limited to specific frequency bands. These alterations suggest disruption of large-scale cortical networks in AD and MCI, which may be limited to specific frequency bands.

Microstates as Disease and Progression Markers in Patients With Mild Cognitive Impairment

Network dysfunction is well established in patients with Alzheimer's disease (AD) and has been shown to be present early in the disease. This is especially interesting in patients with mild cognitive impairment (MCI) since they are more likely to develop AD. In EEG, one type of network analysis is microstates where the EEG is divided into quasi-stable states and these microstates have been linked to networks found with resting state functional MRI. In the current exploratory study, we therefore wanted to explore the changes in microstates in MCI, and AD compared to healthy controls (HC) and whether microstates were able to separate patients with MCI who progressed (pMCI) and those who remained stable (sMCI). EEGs were recorded at baseline for 17 patients with AD, 27 patients with MCI, and 38 older HC and the patients were followed for 3 years. To investigate whole-brain dynamics we extracted different microstate parameters. We found that patients with MCI, and AD had significantly higher occurrence (p-value = 0.028), and coverage (p-value = 0.010) for microstate A compared to HC. However, we did not find any significant systematic deviation of the transition probabilities from randomness for any of the groups. No significant differences were found between pMCI and sMCI but the largest difference in duration was found for microstate D. Microstate A has been linked to the temporal lobes in studies combining EEG and fMRI and the temporal lobes are the most affected by AD pathology in the early stages of the disease. This supports our idea that microstate A may be the first affected microstate in early AD. Even though not significant between pMCI and sMCI, Microstate D has previously been shown to be associated with both frontal and parietal areas as measured with fMRI and may correspond to underlying pathological changes in the progression of MCI to AD. However, larger studies are needed to confirm these findings.