Measurement of precuneal and hippocampal volumes using magnetic resonance volumetry in Alzheimer's disease

Brain morphometry in former American football players: findings from the DIAGNOSE CTE research project

Exposure to repetitive head impacts in contact sports is associated with neurodegenerative disorders including chronic traumatic encephalopathy (CTE), which currently can be diagnosed only at post-mortem. American football players are at higher risk of developing CTE given their exposure to repetitive head impacts. One promising approach for diagnosing CTE in vivo is to explore known neuropathological abnormalities at post-mortem in living individuals using structural MRI. MRI brain morphometry was evaluated in 170 male former American football players ages 45-74 years (n = 114 professional; n = 56 college) and 54 same-age unexposed asymptomatic male controls (n = 54, age range 45-74). Cortical thickness and volume of regions of interest were selected based on established CTE pathology findings and were assessed using FreeSurfer. Group differences and interactions with age and exposure factors were evaluated using a generalized least squares model. A separate logistic regression and independent multinomial model were performed to predict each traumatic encephalopathy syndrome (TES) diagnosis, core clinical features and provisional level of certainty for CTE pathology using brain regions of interest. Former college and professional American football players (combined) showed significant cortical thickness and/or volume reductions compared to unexposed asymptomatic controls in the hippocampus, amygdala, entorhinal cortex, parahippocampal gyrus, insula, temporal pole and superior frontal gyrus. Post hoc analyses identified group-level differences between former professional players and unexposed asymptomatic controls in the hippocampus, amygdala, entorhinal cortex, parahippocampal gyrus, insula and superior frontal gyrus. Former college players showed significant volume reductions in the hippocampus, amygdala and superior frontal gyrus compared to the unexposed asymptomatic controls. We did not observe Age × Group interactions for brain morphometric measures. Interactions between morphometry and exposure measures were limited to a single significant positive association between the age of first exposure to organized tackle football and right insular volume. We found no significant relationship between brain morphometric measures and the TES diagnosis core clinical features and provisional level of certainty for CTE pathology outcomes. These findings suggested that MRI morphometrics detect abnormalities in individuals with a history of repetitive head impact exposure that resemble the anatomic distribution of pathological findings from post-mortem CTE studies. The lack of findings associating MRI measures with exposure metrics (except for one significant relationship) or TES diagnosis and core clinical features suggested that brain morphometry must be complemented by other types of measures to characterize individuals with repetitive head impacts.

Mahmoud L, Sadek I. AI-based tool for early detection of Alzheimer's disease

In the context of Alzheimer's disease (AD), timely identification is paramount for effective management, acknowledging its chronic and irreversible nature, where medications can only impede its progression. Our study introduces a holistic solution, leveraging the hippocampus and the VGG16 model with transfer learning for early AD detection. The hippocampus, a pivotal early affected region linked to memory, plays a central role in classifying patients into three categories: cognitively normal (CN), representing individuals without cognitive impairment; mild cognitive impairment (MCI), indicative of a subtle decline in cognitive abilities; and AD, denoting Alzheimer's disease. Employing the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, our model undergoes training enriched by advanced image preprocessing techniques, achieving outstanding accuracy (testing 98.17 %, validation 97.52 %, training 99.62 %). The strategic use of transfer learning fortifies our competitive edge, incorporating the hippocampus approach and, notably, a progressive data augmentation technique. This innovative augmentation strategy gradually introduces augmentation factors during training, significantly elevating accuracy and enhancing the model's generalization ability. The study emphasizes practical application with a user-friendly website, empowering radiologists to predict class probabilities, track disease progression, and visualize patient images in both 2D and 3D formats, contributing significantly to the advancement of early AD detection.

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links

In recent years, deep learning approaches have gained significant attention in predicting brain disorders using neuroimaging data. However, conventional methods often rely on single-modality data and supervised models, which provide only a limited perspective of the intricacies of the highly complex brain. Moreover, the scarcity of accurate diagnostic labels in clinical settings hinders the applicability of the supervised models. To address these limitations, we propose a novel self-supervised framework for extracting multiple representations from multimodal neuroimaging data to enhance group inferences and enable analysis without resorting to labeled data during pre-training. Our approach leverages Deep InfoMax (DIM), a self-supervised methodology renowned for its efficacy in learning representations by estimating mutual information without the need for explicit labels. While DIM has shown promise in predicting brain disorders from single-modality MRI data, its potential for multimodal data remains untapped. This work extends DIM to multimodal neuroimaging data, allowing us to identify disorder-relevant brain regions and explore multimodal links. We present compelling evidence of the efficacy of our multimodal DIM analysis in uncovering disorder-relevant brain regions, including the hippocampus, caudate, insula, - and multimodal links with the thalamus, precuneus, and subthalamus hypothalamus. Our self-supervised representations demonstrate promising capabilities in predicting the presence of brain disorders across a spectrum of Alzheimer's phenotypes. Comparative evaluations against state-of-the-art unsupervised methods based on autoencoders, canonical correlation analysis, and supervised models highlight the superiority of our proposed method in achieving improved classification performance, capturing joint information, and interpretability capabilities. The computational efficiency of the decoder-free strategy enhances its practical utility, as it saves compute resources without compromising performance. This work offers a significant step forward in addressing the challenge of understanding multimodal links in complex brain disorders, with potential applications in neuroimaging research and clinical diagnosis.

Well-being is associated with cortical thickness network topology of human brain

BACKGROUND

Living a happy and meaningful life is an eternal topic in positive psychology, which is crucial for individuals' physical and mental health as well as social functioning. Well-being can be subdivided into pleasure attainment related hedonic well-being or emotional well-being, and self-actualization related eudaimonic well-being or psychological well-being plus social well-being. Previous studies have mostly focused on human brain morphological and functional mechanisms underlying different dimensions of well-being, but no study explored brain network mechanisms of well-being, especially in terms of topological properties of human brain morphological similarity network.

METHODS

Therefore, in the study, we collected 65 datasets including magnetic resonance imaging (MRI) and well-being data, and constructed human brain morphological network based on morphological distribution similarity of cortical thickness to explore the correlations between topological properties including network efficiency and centrality and different dimensions of well-being.

RESULTS

We found emotional well-being was negatively correlated with betweenness centrality in the visual network but positively correlated with eigenvector centrality in the precentral sulcus, while the total score of well-being was positively correlated with local efficiency in the posterior cingulate cortex of cortical thickness network.

CONCLUSIONS

Our findings demonstrated that different dimensions of well-being corresponded to different cortical hierarchies: hedonic well-being was involved in more preliminary cognitive processing stages including perceptual and attentional information processing, while hedonic and eudaimonic well-being might share common morphological similarity network mechanisms in the subsequent advanced cognitive processing stages.

Application of 3D Whole-Brain Texture Analysis and the Feature Selection Method Based on within-Class Scatter in the Classification and Diagnosis of Alzheimer's Disease

BACKGROUND

Patients with mild cognitive impairment (MCI) are a high-risk group for Alzheimer's disease (AD). Thus, a reliable prediction of the conversion from MCI to AD based on three-dimensional (3D) texture features of MRI images could help doctors in developing effective treatment protocols.

METHODS

The 3D texture features of the whole-brain were deduced based on the gray-level co-occurrence matrix. Then, the embedded feature selection method based on least squares loss and within-class scatter (LSWCS) was employed to select the optimal subsets of features that were used for binary classification (AD, MCI_C, MCI_S, normal control in pairs) based on SVM. A tenfold cross validation was repeated ten times for each classification. LASSO, fused_LASSO, and group LASSO are used in feature selection step for comparison.

RESULTS

The accuracy and the selected features are the focus of clinical diagnosis reports, indicating that the feature selection algorithm is effective.

Agreement Between Automated and Manual MRI Volumetry in Alzheimer's Disease: A Systematic Review and Meta-Analysis

BACKGROUND

Automated magnetic resonance imaging (MRI) volumetry is a promising tool to evaluate regional brain volumes in dementia and especially Alzheimer's disease (AD).

PURPOSE

To compare automated methods and the gold standard manual segmentation in measuring regional brain volumes on MRI across healthy controls, patients with mild cognitive impairment, and patients with dementia due to AD.

STUDY TYPE

Systematic review and meta-analysis.

DATA SOURCES

MEDLINE, Embase, and PsycINFO were searched through October 2021.

FIELD STRENGTH

1.0 T, 1.5 T, or 3.0 T.

ASSESSMENT

Two review authors independently identified studies for inclusion and extracted data. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).

STATISTICAL TESTS

Standardized mean differences (SMD; Hedges' g) were pooled using random-effects meta-analysis with robust variance estimation. Subgroup analyses were undertaken to explore potential sources of heterogeneity. Sensitivity analyses were conducted to examine the impact of the within-study correlation between effect estimates on the meta-analysis results.

RESULTS

Seventeen studies provided sufficient data to evaluate the hippocampus, lateral ventricles, and parahippocampal gyrus. The pooled SMD for the hippocampus, lateral ventricles, and parahippocampal gyrus were 0.22 (95% CI -0.50 to 0.93), 0.12 (95% CI -0.13 to 0.37), and -0.48 (95% CI -1.37 to 0.41), respectively. For the hippocampal data, subgroup analyses suggested that the pooled SMD was invariant across clinical diagnosis and field strength. Subgroup analyses could not be conducted on the lateral ventricles data and the parahippocampal gyrus data due to insufficient data. The results were robust to the selected within-study correlation value.

DATA CONCLUSION

While automated methods are generally comparable to manual segmentation for measuring hippocampal, lateral ventricle, and parahippocampal gyrus volumes, wide 95% CIs and large heterogeneity suggest that there is substantial uncontrolled variance. Thus, automated methods may be used to measure these regions in patients with AD but should be used with caution.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 3.

The effects of cerebral amyloidopathy on regional glucose metabolism in older adults with depression and mild cognitive impairment while performing memory tasks

Co-occurring depression and mild cognitive impairment (MCI) in older adults are important because they have a high risk of conversion to dementia. In the present study, task-related F-18 fluorodeoxyglucose positron emission tomography (FDG-PET) was used to analyse older adults with concomitant depression and MCI. We recruited 20 older adults with simultaneous depression and MCI and 10 older adults with normal cognition (NC). The Verbal Paired Associates test and digit span test were used for the task-related FDG-PET. The 20 older adults with depression and MCI were classified into two groups based on the F-18 florbetaben PET results: depressed MCI patients with (LLD-MCI-A[+]; n = 11) and without amyloid accumulation (LLD-MCI-A[-]; n = 9). Reduced regional cerebral glucose metabolism (rCMglc) in the left superior frontal region was observed in the LLD-MCI-A(-) group compared with the NC group. Analyses of the NC and LLD-MCI-A(+) groups showed significantly decreased rCMglc in the right inferior parietal and left middle frontal regions in the LLD-MCI-A(+) group. rCMglc in the left precuneus was lower in the LLD-MCI-A(+) group than in the LLD-MCI-A(-) group. Significant correlations between the rCMglc in the right inferior parietal/left precuneus regions and memory task scores were observed based on correlation analyses of NC and LLD-MCI-A(+) groups. The findings in the present study indicate the presence of amyloid accumulation influences glucose metabolism in depressed elderly subjects with MCI while performing cognitive tasks. Task-related FDG-PET examinations may help differentiate MCI associated with depression from comorbid depression in patients with prodromal Alzheimer's disease.

Empathy and Theory of Mind in Alzheimer's Disease: A Meta-analysis

OBJECTIVE

A large literature now shows that Alzheimer's disease (AD) disrupts a number of social cognitive abilities, including social perceptual function and theory of mind (ToM). However, less well understood is how the specific subcomponents of ToM as well as both the broader and specific subcomponents of empathic processing are affected.

METHOD

The current study provides the first meta-analytic review of AD that focuses on both empathy and ToM as broad constructs, as well as their overlapping (cognitive empathy and affective ToM) and distinct (affective empathy and cognitive ToM) subcomponents.

RESULTS

Aggregated across 31 studies, the results revealed that, relative to controls, AD is associated with large-sized deficits in both cognitive ToM (g = 1.09) and affective ToM/cognitive empathy (g = 0.76). However, no statistical differences were found between the AD participants and controls on affective empathic abilities (g = 0.36).

CONCLUSIONS

These data point to a potentially important disconnect between core aspects of social cognitive processing in people with AD. The practical and theoretical implications of these findings are discussed.

MRI Segmentation and Classification of Human Brain Using Deep Learning for Diagnosis of Alzheimer's Disease: A Survey

Many neurological diseases and delineating pathological regions have been analyzed, and the anatomical structure of the brain researched with the aid of magnetic resonance imaging (MRI). It is important to identify patients with Alzheimer's disease (AD) early so that preventative measures can be taken. A detailed analysis of the tissue structures from segmented MRI leads to a more accurate classification of specific brain disorders. Several segmentation methods to diagnose AD have been proposed with varying complexity. Segmentation of the brain structure and classification of AD using deep learning approaches has gained attention as it can provide effective results over a large set of data. Hence, deep learning methods are now preferred over state-of-the-art machine learning methods. We aim to provide an outline of current deep learning-based segmentation approaches for the quantitative analysis of brain MRI for the diagnosis of AD. Here, we report how convolutional neural network architectures are used to analyze the anatomical brain structure and diagnose AD, discuss how brain MRI segmentation improves AD classification, describe the state-of-the-art approaches, and summarize their results using publicly available datasets. Finally, we provide insight into current issues and discuss possible future research directions in building a computer-aided diagnostic system for AD.

Interactions with the integrative memory model

The integrative memory model formalizes a new conceptualization of memory in which interactions between representations and cognitive operations within large-scale cerebral networks generate subjective memory feelings. Such interactions allow to explain the complexity of memory expressions, such as the existence of multiples sources for familiarity and recollection feelings and the fact that expectations determine how one recognizes previously encountered information.

Sex Differences in the Complexity of Healthy Older Adults' Magnetoencephalograms

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

The Application of Unsupervised Clustering Methods to Alzheimer's Disease

Clustering is a powerful machine learning tool for detecting structures in datasets. In the medical field, clustering has been proven to be a powerful tool for discovering patterns and structure in labeled and unlabeled datasets. Unlike supervised methods, clustering is an unsupervised method that works on datasets in which there is no outcome (target) variable nor is anything known about the relationship between the observations, that is, unlabeled data. In this paper, we focus on studying and reviewing clustering methods that have been applied to datasets of neurological diseases, especially Alzheimer’s disease (AD). The aim is to provide insights into which clustering technique is more suitable for partitioning patients of AD based on their similarity. This is important as clustering algorithms can find patterns across patients that are difficult for medical practitioners to find. We further discuss the implications of the use of clustering algorithms in the treatment of AD. We found that clustering analysis can point to several features that underlie the conversion from early-stage AD to advanced AD. Furthermore, future work can apply semi-clustering algorithms on AD datasets, which will enhance clusters by including additional information.

Regional glucose metabolism due to the presence of cerebral amyloidopathy in older adults with depression and mild cognitive impairment

BACKGROUND

Depression is a risk factor for mild cognitive impairment (MCI) and for the conversion from MCI to Alzheimer's disease (AD). This study investigated regional cerebral glucose metabolism (rCMglc) in older adults with depression and MCI, either with or without amyloidopathy.

METHODS

We recruited 31 older adults diagnosed with depression and MCI, and 21 older adults with normal cognition (NC). All participants completed demographic questionnaires and were examined with a standardized neuropsychological battery, F-18 fluorodeoxyglucose positron emission tomography (PET), and F-18 florbetaben PET. We classified subjects with depression and MCI into amyloid-β-positive (CDAP; n = 16) and amyloid-β-negative (CDAN; n = 15) groups. Pairwise rCMglc analyses were conducted between all three groups (CDAP vs. NC, CDAN vs. NC, and CDAP vs. CDAN).

RESULTS

In comparison with the NC group, the CDAP group showed reduced rCMglc predominantly in temporoparietal regions, whereas the CDAN group showed lower rCMglc in regions of the frontal lobe, in addition to the temporoparietal regions. The CDAN group also showed lower rCMglc in right anterior cingulate and left inferior orbitofrontal regions, in a comparison between the CDAP and CDAN groups.

LIMITATIONS

The generalizability of the findings is limited because this study has a relatively small number of participants. In addition, this study used cross-sectional design rather than longitudinal design.

CONCLUSIONS

Our findings may provide a reference to assess the risk of future cognitive deterioration. Consequently, this study is expected to contribute to prevention and early identification of dementia associated with AD.

The anteroposterior and primary-to-posterior limbic ratios as MRI-derived volumetric markers of Alzheimer's disease

BACKGROUND/AIMS

Alzheimer's disease (AD) shows a characteristic pattern of brain atrophy, with predominant involvement of posterior limbic structures, and relative preservation of rostral limbic and primary cortical regions. We aimed to investigate the diagnostic utility of two gray matter volume ratios based on this pattern, and to develop a fully automated method to calculate them from unprocessed MRI files.

PATIENTS AND METHODS

Cross-sectional study of 118 subjects from the ADNI database, including normal controls and patients with mild cognitive impairment (MCI) and AD. Clinical variables and 3T T1-weighted MRI files were analyzed. Regional gray matter and total intracranial volumes were calculated with a shell script (gm_extractor) based on FSL. Anteroposterior and primary-to-posterior limbic ratios (APL and PPL) were calculated from these values. Diagnostic utility of variables was tested in logistic regression models using Bayesian model averaging for variable selection. External validity was evaluated with bootstrap sampling and a test set of 60 subjects.

RESULTS

gm_extractor showed high test-retest reliability and high concurrent validity with FSL's FIRST. Volumetric measurements agreed with the expected anatomical pattern associated with AD. APL and PPL ratios were significantly different between groups, and were selected instead of hippocampal and entorhinal volumes to differentiate normal from MCI or cognitively impaired (MCI plus AD) subjects.

CONCLUSION

APL and PPL ratios may be useful components of models aimed to differentiate normal subjects from patients with MCI or AD. These values, and other gray matter volumes, may be reliably calculated with gm_extractor.

Cerebral Perfusion Changes after Acetyl-L-Carnitine Treatment in Early Alzheimer's Disease Using Single Photon Emission Computed Tomography

Background and Purpose

Although acetyl-L-carnitine (ALC) treatment may have beneficial effects on Alzheimer's disease (AD), its underlying neural correlates remain unclear. The purpose of this study was to investigate cerebral perfusion changes after ALC treatment in AD patients using technetium-⁹⁹m hexamethylpropylene amine oxime single photon emission computed tomography (SPECT).

Methods

A total of 18 patients with early AD were prospectively recruited and treated with ALC at 1.5 g/day for 1.4±0.3 years. At baseline and follow-up, brain SPECT, Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR), Global Deterioration Scale (GDS), and Neuropsychiatric Inventory (NPI) were used to assess participants. After ALC administration, changes in brain perfusion, severity of dementia, cognitive performance, and neuropsychiatric disturbances were examined.

Results

After ALC administration, changes in scores of MMSE, CDR, GDS, and NPI were not statistically significant (p>0.05). Voxel-wise whole-brain image analysis revealed that perfusion was significantly (p<0.001) increased in the right precuneus whereas perfusion was reduced in the left inferior temporal gyrus (p<0.001), the right middle frontal gyrus (p<0.001), and the right insular cortex (p=0.001) at follow-up.

Conclusions

Although previous studies have suggested that AD patients generally demonstrate progressive deterioration in brain perfusion and clinical symptoms, this study reveals that the perfusion of the precuneus is increased in AD patients after ALC administration and their cognitive and neuropsychiatric symptoms are not aggravated. Further studies are warranted to determine the potential association between perfusion increase in the precuneus and clinical symptoms after ALC treatment in AD patients.

Electroencephalography-driven approach to prodromal Alzheimer's disease diagnosis: from biomarker integration to network-level comprehension

Decay of the temporoparietal cortex is associated with prodromal Alzheimer's disease (AD). Additionally, shrinkage of the temporoparietal cerebral area has been connected with an increase in α3/α2 electroencephalogram (EEG) power ratio in prodromal AD. Furthermore, a lower regional blood perfusion has been exhibited in patients with a higher α3/α2 proportion when contrasted with low α3/α2 proportion. Furthermore, a lower regional blood perfusion and reduced hippocampal volume has been exhibited in patients with higher α3/α2 when contrasted with lower α3/α2 EEG power ratio. Neuropsychological evaluation, EEG recording, and magnetic resonance imaging were conducted in 74 patients with mild cognitive impairment (MCI). Estimation of cortical thickness and α3/α2 frequency power ratio was conducted for each patient. A subgroup of 27 patients also underwent single-photon emission computed tomography evaluation. In view of α3/α2 power ratio, the patients were divided into three groups. The connections among cortical decay, cerebral perfusion, and memory loss were evaluated by Pearson's r coefficient. Results demonstrated that higher α3/α2 frequency power ratio group was identified with brain shrinkage and cutdown perfusion inside the temporoparietal projections. In addition, decay and cutdown perfusion rate were connected with memory shortfalls in patients with MCI. MCI subgroup with higher α3/α2 EEG power ratio are at a greater risk to develop AD dementia.

Association of EEG, MRI, and regional blood flow biomarkers is predictive of prodromal Alzheimer's disease

BACKGROUND

Thinning in the temporoparietal cortex, hippocampal atrophy, and a lower regional blood perfusion is connected with prodromal stage of Alzheimer's disease (AD). Of note, an increase of electroencephalography (EEG) upper/low alpha frequency power ratio has also been associated with these major landmarks of prodromal AD.

METHODS

Clinical and neuropsychological assessment, EEG recording, and high-resolution three-dimensional magnetic resonance imaging were done in 74 grown up subjects with mild cognitive impairment. This information was gathered and has been assessed 3 years postliminary. EEG recording and perfusion single-photon emission computed tomography assessment was done in 27 subjects. Alpha3/alpha2 frequency power ratio, including cortical thickness, was figured for every subject. Contrasts in cortical thickness among the groups were assessed. Pearson's r relationship coefficient was utilized to evaluate the quality of the relationship between cortical thinning, brain perfusion, and EEG markers.

RESULTS

The higher alpha3/alpha2 frequency power ratio group corresponded with more prominent cortical decay and a lower perfusional rate in the temporoparietal cortex. In a subsequent meetup after 3 years, these patients had AD.

CONCLUSION

High EEG upper/low alpha power ratio was connected with cortical diminishing and lower perfusion in the temporoparietal brain area. The increase in EEG upper/low alpha frequency power ratio could be helpful in recognizing people in danger of conversion to AD dementia and this may be quality information in connection with clinical assessment.

Atrophy and lower regional perfusion of temporo-parietal brain areas are correlated with impairment in memory performances and increase of EEG upper alpha power in prodromal Alzheimer's disease

BACKGROUND

Temporo-parietal cortex thinning is associated with mild cognitive impairment (MCI) due to Alzheimer's disease (AD). The increase of the EEG upper/low alpha power ratio has been associated with MCI due to AD subjects and to the atrophy of temporo-parietal brain areas. Moreover, subjects with a higher alpha3/alpha2 frequency power ratio showed lower brain perfusion than in the low alpha3/alpha2 group. The two groups have significantly different hippocampal volumes and correlation with the theta frequency activity.

METHODS

74 adult subjects with MCI underwent clinical and neuropsychological evaluation, electroencephalogram (EEG) recording, and high resolution 3D magnetic resonance imaging (MRI). 27 of them underwent EEG recording and perfusion single-photon emission computed tomography (SPECT) evaluation. The alpha3/alpha2 power ratio as well as cortical thickness was computed for each subject. The difference in cortical thickness between the groups was estimated. Pearson's r was used to assess the correlation topography between cortical thinning as well as between brain perfusion and memory impairment.

RESULTS

In the higher upper/low alpha group, memory impairment was more pronounced both in the MRI group and the SPECT MCI group. Moreover, it was correlated with greater cortical atrophy and lower perfusional rate in temporo-parietal cortex.

CONCLUSION

High EEG upper/low alpha power ratio was associated with cortical thinning lower perfusion in temporo-parietal. Moreover, atrophy and lower perfusional rate were both significantly correlated with memory impairment in MCI subjects. The increase of EEG upper/low alpha frequency power ratio could be useful for identifying individuals at risk for progression to AD dementia and may be of value in the clinical context.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Theta and alpha EEG frequency interplay in subjects with mild cognitive impairment: evidence from EEG, MRI, and SPECT brain modifications

BACKGROUND

Temporo-parietal and medial temporal cortex atrophy are associated with mild cognitive impairment (MCI) due to Alzheimer disease (AD) as well as the reduction of regional cerebral blood perfusion in hippocampus. Moreover, the increase of EEG alpha3/alpha2 power ratio has been associated with MCI due to AD and with an increase in theta frequency power in a group of subjects with impaired cerebral perfusion in hippocampus.

METHODS

Seventy four adult subjects with MCI underwent clinical and neuropsychological evaluation, electroencephalogram (EEG) recording and high resolution 3D magnetic resonance imaging (MRI). Among the patients, a subset of 27 subjects underwent also perfusion single-photon emission computed tomography and hippocampal atrophy evaluation. Alpha3/alpha2 power ratio as well as cortical thickness was computed for each subject. Three MCI groups were detected according to increasing tertile values of alpha3/alpha2 power ratio and difference of cortical thickness among the groups estimated.

RESULTS

Higher alpha3/alpha2 power ratio group had wider cortical thinning than other groups, mapped to the Supramarginal and Precuneus bilaterally. Subjects with higher alpha3/alpha2 frequency power ratio showed a constant trend to a lower perfusion than lower alpha3/alpha2 group. Moreover, this group correlates with both a bigger hippocampal atrophy and an increase of theta frequency power.

CONCLUSION

Higher EEG alpha3/alpha2 power ratio was associated with temporo-parietal cortical thinning, hippocampal atrophy and reduction of regional cerebral perfusion in medial temporal cortex. In this group an increase of theta frequency power was detected inMCI subjects. The combination of higher EEG alpha3/alpha2 power ratio, cortical thickness measure and regional cerebral perfusion reveals a complex interplay between EEG cerebral rhythms, structural and functional brain modifications.

Electroencephalography reveals lower regional blood perfusion and atrophy of the temporoparietal network associated with memory deficits and hippocampal volume reduction in mild cognitive impairment due to Alzheimer's disease

BACKGROUND

An increased electroencephalographic (EEG) upper/lower alpha power ratio has been associated with less regional blood perfusion, atrophy of the temporoparietal region of the brain, and reduction of hippocampal volume in subjects affected by mild cognitive impairment due to Alzheimer's disease as compared with subjects who do not develop the disease. Moreover, EEG theta frequency activity is quite different in these groups. This study investigated the correlation between biomarkers and memory performance.

METHODS

EEG α3/α2 power ratio and cortical thickness were computed in 74 adult subjects with prodromal Alzheimer's disease. Twenty of these subjects also underwent assessment of blood perfusion by single-photon emission computed tomography (SPECT). Pearson's r was used to assess the correlation between cortical thinning, brain perfusion, and memory impairment.

RESULTS

In the higher α3/α2 frequency power ratio group, greater cortical atrophy and lower regional perfusion in the temporoparietal cortex was correlated with an increase in EEG theta frequency. Memory impairment was more pronounced in the magnetic resonance imaging group and SPECT groups.

CONCLUSION

A high EEG upper/low alpha power ratio was associated with cortical thinning and less perfusion in the temporoparietal area. Moreover, atrophy and less regional perfusion were significantly correlated with memory impairment in subjects with prodromal Alzheimer's disease. The EEG upper/lower alpha frequency power ratio could be useful for identifying individuals at risk for progression to Alzheimer's dementia and may be of value in the clinical context.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Different patterns of brain activation in normal aging and Alzheimer's disease from cognitional sight: meta analysis using activation likelihood estimation

Alzheimer disease (AD) is a chronic neurological disease, frequently affecting cognitional functions. Recently, a large body of neuro-imaging studies have aimed at finding reliable biomarkers of AD for early diagnosis of disease in contrast with healthy elderlies. We intended to have a meta-analytical study on recent functional neuroimaging studies to find the relationship between cognition in AD patients and normal elderlies. A systematic search was conducted to collect functional neuroimaging studies such as positron emission therapy (PET) and functional magnetic resonance imaging (fMRI) in AD patients and healthy elderlies. The coordinates of regions related to cognition were meta-analyzed using the activation likelihood estimation (ALE) method and Sleuth software. P-value map at the false discovery rate (FDR) of P<0.05 thresholds and the clusters with a minimum size of 200 mm(3) were considered. Data were visualized with MANGO software. Forty-one articles that explored the areas activated during cognition in normal elderly subjects and AD patients were found. According to the findings, left middle frontal gyrus and left precuneus are the most activated areas in cognitional tasks in healthy elderlies and AD patients respectively. In normal elderly subjects and AD patients, comparison of ALE maps and reverse contrast showed that insula and left precuneus were the most activated areas in cognitional aspects respectively. With respect to unification of left precuneus activation in cognitional tasks, it seems that this point can be a hallmark in primary differentiation of AD and healthy individuals.

Electroencephalographic upper/low alpha frequency power ratio relates to cortex thinning in mild cognitive impairment

OBJECTIVE

Temporoparietal cortex thinning is associated with mild cognitive impairment (MCI) due to Alzheimer disease (AD). The increase in EEG upper/low α frequency power ratio has been associated with AD converter MCI subjects. We investigated the association of the EEG upper/low α frequency power ratio with patterns of cortical thickness in MCI.

METHODS

74 adult subjects with MCI underwent clinical and neuropsychological evaluation, electroencephalography (EEG) recording and high-resolution 3-dimensional magnetic resonance imaging (MRI). The EEG upper/low α frequency power ratio as well as cortical thickness were computed for each subject. Three MCI groups were detected according to increasing tertile values of EEG upper/low α frequency power ratios, and the difference of cortical thickness among the groups was estimated.

RESULTS

The EEG high upper/low α frequency power ratio group had a total cortical grey matter volume reduction of 471 mm(2), greater than that of the EEG low upper/low α frequency power ratio group (p < 0.001). The EEG high upper/low α frequency power ratio group showed a similar but less marked pattern (160 mm(2)) of cortical thinning when compared to the EEG middle upper/low α frequency power ratio group (p < 0.001). Moreover, the EEG high upper/low α frequency power ratio group had wider cortical thinning than other groups, mapped to the supramarginal gyrus and precuneus bilaterally. No significant regional cortical thickness differences were found between middle and low EEG upper/low α frequency power ratio groups.

CONCLUSION

A high EEG upper/low α frequency power ratio was associated with temporoparietal cortical thinning in MCI subjects. The combination of upper/low α frequency power ratio and cortical thickness measurement could be useful for identifying individuals at risk for progression to AD dementia and may be of value in the clinical context.

EEG upper/low alpha frequency power ratio relates to temporo-parietal brain atrophy and memory performances in mild cognitive impairment

OBJECTIVE

Temporo-parietal cortex thinning is associated to mild cognitive impairment (MCI) due to Alzheimer disease (AD). The increase of EEG upper/low alpha power ratio has been associated with AD-converter MCI subjects. We investigated the association of alpha3/alpha2 ratio with patterns of cortical thickness in MCI.

MATERIALS AND METHODS

Seventy-four adult subjects with MCI underwent clinical and neuropsychological evaluation, electroencephalogram (EEG) recording and high resolution 3D magnetic resonance imaging. Alpha3/alpha2 power ratio as well as cortical thickness was computed for each subject. Three MCI groups were detected according to increasing tertile values of upper/low alpha power ratio. Difference of cortical thickness among the groups was estimated. Pearson's r was used to assess the topography of the correlation between cortical thinning and memory impairment.

RESULTS

High upper/low alpha power ratio group had total cortical gray matter volume reduction of 471 mm(2) than low upper/low alpha power ratio group (p < 0.001). Upper/low alpha group showed a similar but less marked pattern (160 mm(2)) of cortical thinning when compared to middle upper/low alpha power ratio group (p < 0.001). Moreover, high upper/low alpha group had wider cortical thinning than other groups, mapped to the Supramarginal and Precuneus bilaterally. Finally, in high upper/low alpha group temporo-parietal cortical thickness was correlated to memory performance. No significant cortical thickness differences was found between middle and low alpha3/alpha2 power ratio groups.

CONCLUSION

High EEG upper/low alpha power ratio was associated with temporo-parietal cortical thinning and memory impairment in MCI subjects. The combination of EEG upper/low alpha ratio and cortical thickness measure could be useful for identifying individuals at risk for progression to AD dementia and may be of value in clinical context.

Usefulness of medial temporal lobe atrophy visual rating scale in detecting Alzheimer's disease: Preliminary study

Background:

The Korean version of Mini-Mental Status Examination (K-MMSE) and the Korean version of Addenbrooke Cognitive Examination (K-ACE) have been validated as quick neuropsychological tests for screening dementia in various clinical settings. Medial temporal atrophy (MTA) is an early pathological characteristic of Alzheimer's disease (AD). We aimed to assess the diagnostic validity of the fusion of the neuropsychological test and visual rating scale (VRS) of MTA in AD.

Materials and Methods:

A total of fifty subjects (25 AD, 25 controls) were included. The neuropsychological tests used were the K-MMSE and the K-ACE. T1 axial imaging visual rating scale (VRS) was applied for assessing the grade of MTA. We calculated the fusion score with the difference of neuropsychological test and VRS of MTA. The receiver operating characteristics (ROC) curve was used to determine optimal cut-off score, sensitivity and specificity of the fusion scores in screening AD.

Results:

No significant differences in age, gender and education were found between AD and control group. The values of K-MMSE, K-ACE, CDR, VRS and cognitive function test minus VRS were significantly lower in the AD group than control group. The AUC (Area under the curve), sensitivity and specificity for K-MMSE minus VRS were 0.857, 84% and 80% and for K-ACE minus VRS were 0.884, 80% and 88%, respectively. Those for K-MMSE only were 0.842, 76% and 72% and for K-ACE only were 0.868, 80% and 88%, respectively.

Conclusions:

The fusion of the neuropsychological test and VRS suggested clinical usefulness in their easy and superiority over neuropsychological test only. However, this study failed to find any difference. This may be because of small numbers in the study or because there is no true difference.

Sun ginseng protects endothelial progenitor cells from senescence associated apoptosis

Endothelial progenitor cells (EPC) are a population of cells that circulate in the blood stream. They play a role in angiogenesis and, therefore, can be prognostic markers of vascular repair. Ginsenoside Rg₃ prevents endothelial cell apoptosis through the inhibition of the mitochondrial caspase pathway. It also affects estrogen activity, which reduces EPC senescence. Sun ginseng (SG), which is heat-processed ginseng, has a high content of ginsenosides. The purpose of this study was to investigate the protective effects of SG on senescence-associated apoptosis in EPCs. In order to isolate EPCs, mononuclear cells of human blood buffy coats were cultured and characterized by their uptake of acetylated low-density lipoprotein (acLDL) and their binding of Ulex europaeus agglutinin I (ulex-lectin). Flow cytometry with annexin-V staining was performed in order to assess early and late apoptosis. Senescence was determined by β-galactosidase (β-gal) staining. Staining with 4′-6-Diamidino-2-phenylindole verified that most adherent cells (93±2.7%) were acLDL-positive and ulex-lectin-positive. The percentage of β-gal-positive EPCs was decreased from 93.8±2.0% to 62.5±3.6% by SG treatment. A fluorescence-activated cell sorter (FACS) analysis showed that 4.9% of EPCs were late apoptotic in controls. Sun ginseng decreased the apoptotic cell population by 39% in the late stage of apoptosis from control baseline levels. In conclusion, these results show antisenescent and antiapoptotic effects of SG in human-derived EPCs, indicating that SG can enhance EPC-mediated repair mechanisms.

Brain-derived neurotrophic factor gene polymorphisms, neurotransmitter levels, and depressive symptoms in an elderly population

A large number of studies have examined associations between brain-derived neurotrophic factor (BDNF) gene polymorphisms and depressive symptoms. However, results still remain controversial. Recent studies suggested a significant age and gender effect on the heritability of depression. The potential neurobiological pathways that could possibly mediate this relationship have not been examined so far. Since BDNF is involved in the regulation of neurotransmitter production, a mediating role of neurotransmitters seems plausible. The present study aims to examine the association between three common BDNF single-nucleotid polymorphisms (SNPs; rs7103411, rs7124442, and rs6265) and depressive symptoms in a community-based elderly population taking into account the serum levels of four neurotransmitters, serotonin, dopamine, adrenalin, and noradrenalin, as potential mediating factors. We also examined whether age and gender had a modifying effect on this association. We collected and analyzed the genetic and laboratory data as well as Center for Epidemiologic Studies-Depression scores of 350 community-dwelling elderly individuals (aged 65+ years). We found that the BDNF rs6265 polymorphism was related to the severity of depressive symptoms, and that this association was independent of neurotransmitter levels. Stratified analyses showed that this association was restricted to older individuals (≥74 years) and men. The associations of SNPs rs7103411 or rs7124442 SNP with depressive symptoms were not statistically significant. This study importantly adds to the existing literature by affirming previous assumptions on an age and gender difference in the relation between BDNF genotype and depression. We moreover first-time report a missing mediating role of neurotransmitters in this association.

Adverse effects of 24 hours of sleep deprivation on cognition and stress hormones

BACKGROUND AND PURPOSE

The present study was designed to investigate whether 24 h of SD negatively affects the attention and working memory and increases the serum concentrations of stress hormones, glucose, and inflammatory markers.

METHODS

The acute effects of sleep deprivation (SD) on cognition and the stress hormones were evaluated in six healthy volunteers (all men, age 23-27 years). All were good sleepers, had no history of medical or neuropsychiatric diseases, and were not taking any kind of medication. All of the volunteers were subjected to the Continuous Performance Test (CPT) for attention and working memory of cognition and blood tests both before and after 24 h of SD. Electroencephalographic monitoring was performed during the study to confirm the wakefulness of the subjects.

RESULTS

SD significantly elevated the serum concentrations of stress hormones (cortisol, epinephrine, and norepinephrine), but serum levels of glucose and inflammatory markers were not changed compared to baseline. For easier steps of the CPT the subjects performed well in giving correct responses after SD; the correct response scores decreased only at the most difficult step of the CPT. However, the subjects performed consistently poor for the error responses at all steps after SD. There was no correlation between the CPT scores and stress hormone levels.

CONCLUSIONS

The 24 h of SD significantly heightened the levels of stress hormones and lowered attention and working memory. The acute SD condition seems to render the subject more susceptible to making errors.

Functional connectivity mapping of the human precuneus by resting state fMRI

Precuneus responds to a wide range of cognitive processes. Here, we examined how the patterns of resting state connectivity may define functional subregions in the precuneus. Using a K-means algorithm to cluster the whole-brain "correlograms" of the precuneus in 225 adult individuals, we corroborated the dorsal-anterior, dorsal-posterior, and ventral subregions, each involved in spatially guided behaviors, mental imagery, and episodic memory as well as self-related processing, with the ventral precuneus being part of the default mode network, as described extensively in earlier work. Furthermore, we showed that the lateral/medial volumes of dorsal anterior and dorsal posterior precuneus are each connected with areas of motor execution/attention and motor/visual imagery, respectively. Compared to the ventral precuneus, the dorsal precuneus showed greater connectivity with occipital and posterior parietal cortices, but less connectivity with the medial superior frontal and orbitofrontal gyri, anterior cingulate cortex as well as the parahippocampus. Compared to dorsal-posterior and ventral precuneus, the dorsal-anterior precuneus showed greater connectivity with the somatomotor cortex, as well as the insula, supramarginal, Heschl's, and superior temporal gyri, but less connectivity with the angular gyrus. Compared to ventral and dorsal-anterior precuneus, dorsal-posterior precuneus showed greater connectivity with the middle frontal gyrus. Notably, the precuneus as a whole has negative connectivity with the amygdala and the lateral and inferior orbital frontal gyri. Finally, men and women differed in the connectivity of precuneus. Men and women each showed greater connectivity with the dorsal precuneus in the cuneus and medial thalamus, respectively. Women also showed greater connectivity with ventral precuneus in the hippocampus/parahippocampus, middle/anterior cingulate gyrus, and middle occipital gyrus, compared to men. Taken together, these new findings may provide a useful platform upon which to further investigate sex-specific functional neuroanatomy of the precuneus and to elucidate the pathology of many neurological illnesses.