Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer's disease

Cortical thickness and grey-matter volume anomaly detection in individual MRI scans: Comparison of two methods

Over the past decades, morphometric analysis of brain MRI has contributed substantially to the understanding of healthy brain structure, development and aging as well as to improved characterisation of disease related pathologies. Certified commercial tools based on normative modeling of these metrics are meanwhile available for diagnostic purposes, but they are cost intensive and their clinical evaluation is still in its infancy. Here we have compared the performance of "ScanOMetrics", an open-source research-level tool for detection of statistical anomalies in individual MRI scans, depending on whether it is operated on the output of FreeSurfer or of the deep learning based brain morphometry tool DL + DiReCT. When applied to the public OASIS3 dataset, containing patients with Alzheimer's disease (AD) and healthy controls (HC), cortical thickness anomalies in patient scans were mainly detected in regions that are known as predilection areas of cortical atrophy in AD, regardless of the software used for extraction of the metrics. By contrast, anomaly detections in HCs were up to twenty-fold reduced and spatially unspecific using both DL + DiReCT and FreeSurfer. Progression of the atrophy pattern with clinical dementia rating (CDR) was clearly observable with both methods. DL + DiReCT provided results in less than 25 min, more than 15 times faster than FreeSurfer. This difference in computation time might be relevant when considering application of this or similar methodology as diagnostic decision support for neuroradiologists.

Cholecystokinin neurotransmission in the central nervous system: Insights into its role in health and disease

Cholecystokinin (CCK) plays a key role in various brain functions, including both health and disease states. Despite the extensive research conducted on CCK, there remain several important questions regarding its specific role in the brain. As a result, the existing body of literature on the subject is complex and sometimes conflicting. The primary objective of this review article is to provide a comprehensive overview of recent advancements in understanding the central nervous system role of CCK, with a specific emphasis on elucidating CCK's mechanisms for neuroplasticity, exploring its interactions with other neurotransmitters, and discussing its significant involvement in neurological disorders. Studies demonstrate that CCK mediates both inhibitory long-term potentiation (iLTP) and excitatory long-term potentiation (eLTP) in the brain. Activation of the GPR173 receptor could facilitate iLTP, while the Cholecystokinin B receptor (CCKBR) facilitates eLTP. CCK receptors' expression on different neurons regulates activity, neurotransmitter release, and plasticity, emphasizing CCK's role in modulating brain function. Furthermore, CCK plays a pivotal role in modulating emotional states, Alzheimer's disease, addiction, schizophrenia, and epileptic conditions. Targeting CCK cell types and circuits holds promise as a therapeutic strategy for alleviating these brain disorders.

Cholecystokinin B receptor agonists alleviates anterograde amnesia in cholecystokinin-deficient and aged Alzheimer's disease mice

BACKGROUND

As one major symptom of Alzheimer's disease (AD), anterograde amnesia describes patients with an inability in new memory formation. The crucial role of the entorhinal cortex in forming new memories has been well established, and the neuropeptide cholecystokinin (CCK) is reported to be released from the entorhinal cortex to enable neocortical associated memory and long-term potentiation. Though several studies reveal that the entorhinal cortex and CCK are related to AD, it is less well studied. It is unclear whether CCK is a good biomarker or further a great drug candidate for AD.

METHODS

mRNA expressions of CCK and CCK-B receptor (CCKBR) were examined in two mouse models, 3xTg AD and CCK knock-out (CCK-/-) mice. Animals' cognition was investigated with Morris water maze, novel object recognition test and neuroplasticity with in-vitro electrophysiological recording. Drugs were given intraperitoneally to animals to investigate the rescue effects on cognitive deficits, or applied to brain slices directly to explore the influence in inducement of long-term potentiation.

RESULTS

Aged 3xTg AD mice exhibited reduced CCK mRNA expression in the entorhinal cortex but reduced CCKBR expression in the neocortex and hippocampus, and impaired cognition and neuroplasticity comparable with CCK-/- mice. Importantly, the animals displayed improved performance and enhanced long-term potentiation after the treatment of CCKBR agonists.

CONCLUSIONS

Here we provide more evidence to support the role of CCK in learning and memory and its potential to treat AD. We elaborated on the rescue effect of a promising novel drug, HT-267, on aged 3xTg AD mice. Although the physiological etiology of CCK in AD still needs to be further investigated, this study sheds light on a potential pharmaceutical candidate for AD and dementia.

Alzheimer's disease progression detection based on optical fluence rate measurements using alternative laser wavelengths

Alzheimer's disease (AD) levels have increased globally, which is considered the sixth reason for deaths. So, a requirement exists for economic and quantitative methods to follow up the gradual progression of AD. The current study presents a simulation for a non-irradiated, safe, wearable, and noninvasive mobile approach for detecting the progression of Alzheimer's brain atrophy using the optical diffusion technique and for investigating the difference between the normal and the diseased brain. The virtual study was accomplished using COMSOL Multiphysics. The simulated head is implemented as the following: scalp, skull, cerebrospinal fluid, gray matter, and white matter. The optical properties of the heterogeneous tissue are observed using the fluence rate after irradiating the head with different wavelengths (630, 700, 810, 915, and 1000 nm) of lasers. Two assessment techniques were applied to evaluate the brain atrophy measurements; the first technique was an array of photodetectors, which were lined at the head posterior, while a matrix of photodetectors was applied over the head surface in the second technique. The results show that the surface photodetectors approach differentiates the normal from AD brains without measuring the brain atrophy percentages by applying 630 nm. The array of photodetectors distinguishes normal from AD brains without detecting the brain atrophy percentages when the wavelengths 630, 700, and 810 nm were applied. The line detector at 1000 nm evaluates the brain atrophy percentages with AD. The future explores applying those techniques in vivo and analyzing the information by the spectrometer for extensively safer early detection of neural disorders.

Combining neuropsychological assessment and structural neuroimaging to identify early Alzheimer's disease in a memory clinic cohort

INTRODUCTION

The current study examined the contributions of comprehensive neuropsychological assessment and volumetric assessment of selected mesial temporal subregions on structural magnetic resonance imaging (MRI) to identify patients with amnestic mild cognitive impairment (aMCI) and mild probable Alzheimer's disease (AD) dementia in a memory clinic cohort.

METHODS

Comprehensive neuropsychological assessment and automated entorhinal, transentorhinal, and hippocampal volume measurements were conducted in 40 healthy controls, 38 patients with subjective memory symptoms, 16 patients with aMCI, 16 patients with mild probable AD dementia. Multinomial logistic regression was used to compare the neuropsychological and MRI measures.

RESULTS

Combining the neuropsychological and MRI measures improved group membership prediction over the MRI measures alone but did not improve group membership prediction over the neuropsychological measures alone.

CONCLUSION

Comprehensive neuropsychological assessment was an important tool to evaluate cognitive impairment. The mesial temporal volumetric MRI measures contributed no diagnostic value over and above the determinations made through neuropsychological assessment.

Exploring morphological similarity and randomness in Alzheimer's disease using adjacent grey matter voxel-based structural analysis

BACKGROUND

Alzheimer's disease is characterized by large-scale structural changes in a specific pattern. Recent studies developed morphological similarity networks constructed by brain regions similar in structural features to represent brain structural organization. However, few studies have used local morphological properties to explore inter-regional structural similarity in Alzheimer's disease.

METHODS

Here, we sourced T1-weighted MRI images of 342 cognitively normal participants and 276 individuals with Alzheimer's disease from the Alzheimer's Disease Neuroimaging Initiative database. The relationships of grey matter intensity between adjacent voxels were defined and converted to the structural pattern indices. We conducted the information-based similarity method to evaluate the structural similarity of structural pattern organization between brain regions. Besides, we examined the structural randomness on brain regions. Finally, the relationship between the structural randomness and cognitive performance of individuals with Alzheimer's disease was assessed by stepwise regression.

RESULTS

Compared to cognitively normal participants, individuals with Alzheimer's disease showed significant structural pattern changes in the bilateral posterior cingulate gyrus, hippocampus, and olfactory cortex. Additionally, individuals with Alzheimer's disease showed that the bilateral insula had decreased inter-regional structural similarity with frontal regions, while the bilateral hippocampus had increased inter-regional structural similarity with temporal and subcortical regions. For the structural randomness, we found significant decreases in the temporal and subcortical areas and significant increases in the occipital and frontal regions. The regression analysis showed that the structural randomness of five brain regions was correlated with the Mini-Mental State Examination scores of individuals with Alzheimer's disease.

CONCLUSIONS

Our study suggested that individuals with Alzheimer's disease alter micro-structural patterns and morphological similarity with the insula and hippocampus. Structural randomness of individuals with Alzheimer's disease changed in temporal, frontal, and occipital brain regions. Morphological similarity and randomness provide valuable insight into brain structural organization in Alzheimer's disease.

Integrating Biomarkers From Virtual Reality and Magnetic Resonance Imaging for the Early Detection of Mild Cognitive Impairment Using a Multimodal Learning Approach: Validation Study

BACKGROUND

Early detection of mild cognitive impairment (MCI), a transitional stage between normal aging and Alzheimer disease, is crucial for preventing the progression of dementia. Virtual reality (VR) biomarkers have proven to be effective in capturing behaviors associated with subtle deficits in instrumental activities of daily living, such as challenges in using a food-ordering kiosk, for early detection of MCI. On the other hand, magnetic resonance imaging (MRI) biomarkers have demonstrated their efficacy in quantifying observable structural brain changes that can aid in early MCI detection. Nevertheless, the relationship between VR-derived and MRI biomarkers remains an open question. In this context, we explored the integration of VR-derived and MRI biomarkers to enhance early MCI detection through a multimodal learning approach.

OBJECTIVE

We aimed to evaluate and compare the efficacy of VR-derived and MRI biomarkers in the classification of MCI while also examining the strengths and weaknesses of each approach. Furthermore, we focused on improving early MCI detection by leveraging multimodal learning to integrate VR-derived and MRI biomarkers.

METHODS

The study encompassed a total of 54 participants, comprising 22 (41%) healthy controls and 32 (59%) patients with MCI. Participants completed a virtual kiosk test to collect 4 VR-derived biomarkers (hand movement speed, scanpath length, time to completion, and the number of errors), and T1-weighted MRI scans were performed to collect 22 MRI biomarkers from both hemispheres. Analyses of covariance were used to compare these biomarkers between healthy controls and patients with MCI, with age considered as a covariate. Subsequently, the biomarkers that exhibited significant differences between the 2 groups were used to train and validate a multimodal learning model aimed at early screening for patients with MCI among healthy controls.

RESULTS

The support vector machine (SVM) using only VR-derived biomarkers achieved a sensitivity of 87.5% and specificity of 90%, whereas the MRI biomarkers showed a sensitivity of 90.9% and specificity of 71.4%. Moreover, a correlation analysis revealed a significant association between MRI-observed brain atrophy and impaired performance in instrumental activities of daily living in the VR environment. Notably, the integration of both VR-derived and MRI biomarkers into a multimodal SVM model yielded superior results compared to unimodal SVM models, achieving higher accuracy (94.4%), sensitivity (100%), specificity (90.9%), precision (87.5%), and F1-score (93.3%).

CONCLUSIONS

The results indicate that VR-derived biomarkers, characterized by their high specificity, can be valuable as a robust, early screening tool for MCI in a broader older adult population. On the other hand, MRI biomarkers, known for their high sensitivity, excel at confirming the presence of MCI. Moreover, the multimodal learning approach introduced in our study provides valuable insights into the improvement of early MCI detection by integrating a diverse set of biomarkers.

A nonhuman primate model with Alzheimer's disease-like pathology induced by hippocampal overexpression of human tau

BACKGROUND

Alzheimer's disease (AD) is one of the most burdening diseases of the century with no disease-modifying treatment at this time. Nonhuman primates (NHPs) share genetic, anatomical, and physiological similarities with humans, making them ideal model animals for investigating the pathogenesis of AD and potential therapies. However, the use of NHPs in AD research has been hindered by the paucity of AD monkey models due to their long generation time, ethical considerations, and technical challenges in genetically modifying monkeys.

METHODS

Here, we developed an AD-like NHP model by overexpressing human tau in the bilateral hippocampi of adult rhesus macaque monkeys. We evaluated the pathological features of these monkeys with immunostaining, Nissl staining, cerebrospinal fluid (CSF) analysis, magnetic resonance imaging (MRI), positron emission tomography (PET), and behavioural tests.

RESULTS

We demonstrated that after hippocampal overexpression of tau protein, these monkeys displayed multiple pathological features of AD, including 3-repeat (3R)/4-repeat (4R) tau accumulation, tau hyperphosphorylation, tau propagation, neuronal loss, hippocampal atrophy, neuroinflammation, Aβ clearance deficits, blood vessel damage, and cognitive decline. More interestingly, the accumulation of both 3R and 4R tau is specific to NHPs but not found in adult rodents.

CONCLUSIONS

This work establishes a tau-induced AD-like NHP model with many key pathological and behavioural features of AD. In addition, our model may potentially become one of the AD NHP models adopted by researchers worldwide since it can be generated within 2 ~ 3 months through a single injection of AAVs into the monkey brains. Hence, our model NHPs may facilitate mechanistic studies and therapeutic treatments for AD.

Gait smoothness during high-demand motor walking tasks in older adults with mild cognitive impairment

Early signs of Mild Cognitive Impairment (MCI)-related gait deficits may be detected through the performance of complex walking tasks that require high gait control. Gait smoothness is a robust metric of overall body stability during walking. This study aimed to explore gait smoothness during complex walking tasks in older adults with and without MCI. Participants were 18 older adults with MCI (mean age = 67.89 ± 4.64 years) and 18 cognitively intact controls (mean age = 67.72 ± 4.63 years). Gait assessment was conducted under four complex walking tasks: walking a narrow path, walking around an obstacle, horizontal head turns while walking, and vertical head turns while walking. The index of harmonicity (IH), representing gait smoothness associated with overall body stability, was measured in anteroposterior, mediolateral, and vertical directions. A multivariate analysis was employed to compare the differences in IH between groups for each complex walking task. The MCI group demonstrated a reduction of IH in the mediolateral direction during the horizontal head turns than the control group (MCI group = 0.64 ± 0.16, Control group = 0.74 ± 0.12, p = 0.04). No significant differences between groups were found for the IH in other directions or walking conditions. These preliminary findings indicate that older adults with MCI have a decline in step regularity in the mediolateral direction during walking with horizontal head turns. Assessment of the smoothness of walking during head turns may be a useful approach to identifying subtle gait alterations in older adults with MCI, which may facilitate timely gait intervention.

Olfactory Dysfunction Associated with Cognitive Decline in an Elderly Population

BACKGROUND

In many neurological disorders, including Alzheimer disease, early olfactory dysfunction is observed.

OBJECTIVE

In order to determine if deficits in olfactory memory are present in the elderly and if olfactory dysfunction correlates with cognitive impairment in the aging population, olfactory testing has been done on seniors from the NuAge cohort accepting to participate in the Olfactory Response Cognition and Aging (ORCA) secondary sub-study. The t-Mini Mental Statement Examination and the Telephone Interview for Cognitive Status tests were done to assess cognition levels.

RESULTS

Overall, 94% of the ORCA cohort displayed olfactory dysfunction. Deficits in olfactory memory were also present. A correlation was observed between olfactory function and cognitive test scores. Moreover, in women who smoked, there was an association between olfactory memory and cognitive scores.

CONCLUSION

Our results suggest that olfactory dysfunction may predict impending cognitive decline and highlights the need for olfactory training in seniors to improve olfaction and overall well-being.

Comparing Symmetric Dimethylarginine and Amyloid-β42 as Predictors of Alzheimer's Disease Development

Background

Physicians may soon be able to diagnose Alzheimer's disease (AD) in its early stages using fluid biomarkers like amyloid. However, it is acknowledged that additional biomarkers need to be characterized which would facilitate earlier monitoring of AD pathogenesis.

Objective

To determine if a potential novel inflammation biomarker for AD, symmetric dimethylarginine, has utility as a baseline serum biomarker for discriminating prodromal AD from cognitively unimpaired controls in comparison to cerebrospinal fluid amyloid-β42 (Aβ42).

Methods

Data including demographics, magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography scans, Mini-Mental State Examination and Functional Activities Questionnaire scores, and biomarker concentrations were obtained from the Alzheimer's Disease Neuroimaging Initiative for a total of 146 prodromal AD participants and 108 cognitively unimpaired controls.

Results

Aβ42 (p = 0.65) and symmetric dimethylarginine (p = 0.45) were unable to predict age-matched cognitively unimpaired controls and prodromal AD participants. Aβ42 was negatively associated with regional brain atrophy and hypometabolism as well as cognitive and functional decline in cognitively unimpaired control participants (p < 0.05) that generally decreased in time. There were no significant associations between Aβ42 and symmetric dimethylarginine with imaging or neurocognitive biomarkers in prodromal AD patients.

Conclusions

Correlations were smaller between Aβ42 and neuropathological biomarkers over time and were absent in prodromal AD participants, suggesting a plateau effect dependent on age and disease stage. Evidence supporting symmetric dimethylarginine as a novel biomarker for AD as a single measurement was not found.

Brain-Cognition Associations in Older Patients With Remitted Major Depressive Disorder or Mild Cognitive Impairment: A Multivariate Analysis of Gray and White Matter Integrity

BACKGROUND

Almost half of older patients with major depressive disorder (MDD) present with cognitive impairment, and one-third meet diagnostic criteria for mild cognitive impairment (MCI). However, mechanisms linking MDD and MCI remain unclear. We investigated multivariate associations between brain structural alterations and cognition in 3 groups of older patients at risk for dementia, remitted MDD (rMDD), MCI, and rMDD+MCI, as well as cognitively healthy nondepressed control participants.

METHODS

We analyzed magnetic resonance imaging data and cognitive domain scores in participants from the PACt-MD (Prevention of Alzheimer's Disease With Cognitive Remediation Plus Transcranial Direct Current Stimulation in Mild Cognitive Impairment and Depression) study. Following quality control, we measured cortical thickness and subcortical volumes of selected regions from 283 T1-weighted scans and fractional anisotropy of white matter tracts from 226 diffusion-weighted scans. We assessed brain-cognition associations using partial least squares regressions in the whole sample and in each subgroup.

RESULTS

In the entire sample, atrophy in the medial temporal lobe and subregions of the motor and prefrontal cortex was associated with deficits in verbal and visuospatial memory, language skills, and, to a lesser extent, processing speed (p < .0001; multivariate r = 0.30, 0.34, 0.26, and 0.18, respectively). Widespread reduced white matter integrity was associated with deficits in executive functioning, working memory, and processing speed (p = .008; multivariate r = 0.21, 0.26, 0.35, respectively). Overall, associations remained significant in the MCI and rMDD+MCI groups, but not the rMDD or healthy control groups.

CONCLUSIONS

We confirm findings of brain-cognition associations previously reported in MCI and extend them to rMDD+MCI, but similar associations in rMDD are not supported. Early-onset and treated MDD might not contribute to structural alterations associated with cognitive impairment.

DMCA-GAN: Dual Multilevel Constrained Attention GAN for MRI-Based Hippocampus Segmentation

Precise segmentation of the hippocampus is essential for various human brain activity and neurological disorder studies. To overcome the small size of the hippocampus and the low contrast of MR images, a dual multilevel constrained attention GAN for MRI-based hippocampus segmentation is proposed in this paper, which is used to provide a relatively effective balance between suppressing noise interference and enhancing feature learning. First, we design the dual-GAN backbone to effectively compensate for the spatial information damage caused by multiple pooling operations in the feature generation stage. Specifically, dual-GAN performs joint adversarial learning on the multiscale feature maps at the end of the generator, which yields an average Dice coefficient (DSC) gain of 5.95% over the baseline. Next, to suppress MRI high-frequency noise interference, a multilayer information constraint unit is introduced before feature decoding, which improves the sensitivity of the decoder to forecast features by 5.39% and effectively alleviates the network overfitting problem. Then, to refine the boundary segmentation effects, we construct a multiscale feature attention restraint mechanism, which forces the network to concentrate more on effective multiscale details, thus improving the robustness. Furthermore, the dual discriminators D1 and D2 also effectively prevent the negative migration phenomenon. The proposed DMCA-GAN obtained a DSC of 90.53% on the Medical Segmentation Decathlon (MSD) dataset with tenfold cross-validation, which is superior to the backbone by 3.78%.

Digital Marker for Early Screening of Mild Cognitive Impairment Through Hand and Eye Movement Analysis in Virtual Reality Using Machine Learning: First Validation Study

BACKGROUND

With the global rise in Alzheimer disease (AD), early screening for mild cognitive impairment (MCI), which is a preclinical stage of AD, is of paramount importance. Although biomarkers such as cerebrospinal fluid amyloid level and magnetic resonance imaging have been studied, they have limitations, such as high cost and invasiveness. Digital markers to assess cognitive impairment by analyzing behavioral data collected from digital devices in daily life can be a new alternative. In this context, we developed a "virtual kiosk test" for early screening of MCI by analyzing behavioral data collected when using a kiosk in a virtual environment.

OBJECTIVE

We aimed to investigate key behavioral features collected from a virtual kiosk test that could distinguish patients with MCI from healthy controls with high statistical significance. Also, we focused on developing a machine learning model capable of early screening of MCI based on these behavioral features.

METHODS

A total of 51 participants comprising 20 healthy controls and 31 patients with MCI were recruited by 2 neurologists from a university hospital. The participants performed a virtual kiosk test-developed by our group-where we recorded various behavioral data such as hand and eye movements. Based on these time series data, we computed the following 4 behavioral features: hand movement speed, proportion of fixation duration, time to completion, and the number of errors. To compare these behavioral features between healthy controls and patients with MCI, independent-samples 2-tailed t tests were used. Additionally, we used these behavioral features to train and validate a machine learning model for early screening of patients with MCI from healthy controls.

RESULTS

In the virtual kiosk test, all 4 behavioral features showed statistically significant differences between patients with MCI and healthy controls. Compared with healthy controls, patients with MCI had slower hand movement speed (t49=3.45; P=.004), lower proportion of fixation duration (t49=2.69; P=.04), longer time to completion (t49=-3.44; P=.004), and a greater number of errors (t49=-3.77; P=.001). All 4 features were then used to train a support vector machine to distinguish between healthy controls and patients with MCI. Our machine learning model achieved 93.3% accuracy, 100% sensitivity, 83.3% specificity, 90% precision, and 94.7% F1-score.

CONCLUSIONS

Our research preliminarily suggests that analyzing hand and eye movements in the virtual kiosk test holds potential as a digital marker for early screening of MCI. In contrast to conventional biomarkers, this digital marker in virtual reality is advantageous as it can collect ecologically valid data at an affordable cost and in a short period (5-15 minutes), making it a suitable means for early screening of MCI. We call for further studies to confirm the reliability and validity of this approach.

Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection

Alzheimer's disease (AD) leads to irreversible cognitive decline, with Mild Cognitive Impairment (MCI) as its prodromal stage. Early detection of AD and related dementia is crucial for timely treatment and slowing disease progression. However, classifying cognitive normal (CN), MCI, and AD subjects using machine learning models faces class imbalance, necessitating the use of balanced accuracy as a suitable metric. To enhance model performance and balanced accuracy, we introduce a novel method called VS-Opt-Net. This approach incorporates the recently developed vector-scaling (VS) loss into a machine learning pipeline named STREAMLINE. Moreover, it employs Bayesian optimization for hyperparameter learning of both the model and loss function. VS-Opt-Net not only amplifies the contribution of minority examples in proportion to the imbalance level but also addresses the challenge of generalization in training deep networks. In our empirical study, we use MRI-based brain regional measurements as features to conduct the CN vs MCI and AD vs MCI binary classifications. We compare the balanced accuracy of our model with other machine learning models and deep neural network loss functions that also employ class-balanced strategies. Our findings demonstrate that after hyperparameter optimization, the deep neural network using the VS loss function substantially improves balanced accuracy. It also surpasses other models in performance on the AD dataset. Moreover, our feature importance analysis highlights VS-Opt-Net's ability to elucidate biomarker differences across dementia stages.

Recent diagnostic techniques for the detection of Alzheimer's disease: a short review

Alzheimer's disease (AD) is a neurological condition that affects millions of individuals around the world and for which there are few effective therapies. Dementia is characterized by the formation of senile plaques and neurofibrillary tangles, which is followed by neurotoxicity, which results in memory loss and mortality. Pathogenesis occurs several years before the onset of disease. As the disease-modifying drugs are most effective in the early stages of Alzheimer's disease, biomarkers for early detection of disease and their development are crucial. This review discusses the diagnostic utility, benefits, and limitations of traditional techniques such as neuroimaging, cognitive testing, positron emission tomography, and biomarkers, as well as the novel techniques such as artificial intelligence, machine learning, immunotherapy, and blood test approaches for early detection, understanding, and treatment of AD.

The Effects of Ninjinyoeito on Impaired Spatial Memory and Prefrontal Cortical Synaptic Plasticity through α-Amino-3-hydroxy-5-4-isoxazole Propionic Acid Receptor Subunit in a Rat Model with Cerebral Ischemia and β-Amyloid Injection

Ninjinyoeito (NYT), a traditional Japanese medicine, is effective for improving physical strength and treating fatigue and anorexia. Recently, a clinical report revealed that NYT ameliorates cognitive dysfunction in Alzheimer's disease (AD) patients, although the mechanisms remain unclear. AD is a neurodegenerative disorder accompanied by a progressive deficit in memory. Current therapeutic agents are largely ineffective in treating cognitive dysfunction in AD patients. In this study, we investigated the effects of NYT on spatial memory impairment in a rat model of dementia. Rats were prepared with transient cerebral ischemia and intraventricular injection of β-amyloid1-42 for 7 days (CI + Aβ). NYT was orally administered for 7 days after cerebral ischemia. We evaluated spatial memory using the Morris water maze and investigated the expression of α-amino-3-hydroxy-5-4-isoxazole propionic acid receptor subunits, the phosphorylation level of glutamate receptor A (GluA)1 at serine sites S831 and S845, and the Ca2+/calmodulin-dependent protein kinase II (CaMKII) in the hippocampus and prefrontal cortex of CI + Aβ rats. In the CI + Aβ rats, NYT treatment shortened the extended time to reach the platform. However, NYT did not restore the decrease in the hippocampal GluA1, GluA2, or CaMKII expression but increased prefrontal cortical phosphorylation levels of S845-GluA1 and CaMKII. Therefore, NYT may alleviate spatial memory impairment by promoting glutamatergic transmission involved in the phosphorylation of S845-GluA1 and CaMKII in the prefrontal cortex of CI + Aβ rats. Our results suggest that NYT is a valuable treatment for AD patients.

Procedural learning and retention relative to explicit learning and retention in mild cognitive impairment and Alzheimer's disease using a modification of the trail making test

Amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) dementia are characterized by pathological changes to the medial temporal lobes, resulting in explicit learning and retention reductions. Studies demonstrate that implicit/procedural memory processes are relatively intact in these populations, supporting different anatomical substrates for differing memory systems. This study examined differences between explicit and procedural learning and retention in individuals with aMCI and AD dementia relative to matched healthy controls. We also examined anatomical substrates using volumetric MRI. Results revealed expected difficulties with explicit learning and retention in individuals with aMCI and AD with relatively preserved procedural memory. Explicit verbal retention was associated with medial temporal cortex volumes. However, procedural retention was not related to medial temporal or basal ganglia volumes. Overall, this study confirms the dissociation between explicit relative to procedural learning and retention in aMCI and AD dementia and supports differing anatomical substrates.

Asynchronous functional linear regression models for longitudinal data in reproducing kernel Hilbert space

Motivated by the analysis of longitudinal neuroimaging studies, we study the longitudinal functional linear regression model under asynchronous data setting for modeling the association between clinical outcomes and functional (or imaging) covariates. In the asynchronous data setting, both covariates and responses may be measured at irregular and mismatched time points, posing methodological challenges to existing statistical methods. We develop a kernel weighted loss function with roughness penalty to obtain the functional estimator and derive its representer theorem. The rate of convergence, a Bahadur representation, and the asymptotic pointwise distribution of the functional estimator are obtained under the reproducing kernel Hilbert space framework. We propose a penalized likelihood ratio test to test the nullity of the functional coefficient, derive its asymptotic distribution under the null hypothesis, and investigate the separation rate under the alternative hypotheses. Simulation studies are conducted to examine the finite-sample performance of the proposed procedure. We apply the proposed methods to the analysis of multitype data obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, which reveals significant association between 21 regional brain volume density curves and the cognitive function. Data used in preparation of this paper were obtained from the ADNI database (adni.loni.usc.edu).

Frontal and temporal lobe correlates of verbal learning and memory in aMCI and suspected Alzheimer's disease dementia

Alzheimer's disease is primarily known for deficits in learning and retaining new information. This has long been associated with pathological changes in the mesial temporal lobes. The role of the frontal lobes in memory in Alzheimer's disease is less well understood. In this study, we examined the role of the frontal lobes in learning, recognition, and retention of new verbal information, as well as the presence of specific errors (i.e., intrusions and false-positive errors). Participants included one hundred sixty-seven patients clinically diagnosed with amnestic mild cognitive impairment or suspected Alzheimer's disease dementia who were administered the California Verbal Learning Test and completed high-resolution MRI. We confirmed the role of the mesial temporal lobes in learning and retention, including the volumes of the hippocampus, entorhinal cortex, and parahippocampal gyrus. In addition, false-positive errors were associated with all volumes of the mesial temporal lobes and widespread areas within the frontal lobes. Errors of intrusion were related to the supplementary motor cortex and hippocampus. Most importantly, the mesial temporal lobes interacted with the frontal lobes for learning, recognition, and memory errors. Lower volumes in both regions explained more performance variance than any single structure. This study supports the interaction of the frontal lobes with the temporal lobes in many aspects of memory in Alzheimer's disease.

Relationship between cognitive reserve, brain volume, and neuropsychological performance in amnestic and nonamnestic MCI

Cognitive Reserve (CR) is a theoretical construct that influences the onset and course of cognitive and structural changes that occur with aging and mild cognitive impairment (MCI). There is a paucity of research that examines the relationship of CR and brain volumes in amnestic (aMCI) and nonamnestic (naMCI) separately. This study is a retrospective chart review of MCI patients who underwent neuropsychological evaluation and brain MRI with NeuroReader™ (NR). NR is an FDA-cleared software that standardizes MRI volumes to a control sample. Classifications of aMCI and naMCI were based on Petersen criteria. CR was measured as education, occupation, and word reading. Data analysis included bivariate correlations between CR, neuropsychological test scores, and NR-brain volumes by MCI subtype. The Benjamini-Hochberg method corrected for multiple comparisons. The sample included 91 participants with aMCI and 41 with naMCI. Within naMCI, positive correlations were observed between CR and whole brain volume, total gray matter, bifrontal, left parietal, left occipital, and bilateral cerebellum. Within aMCI, no significant correlations were observed between CR and brain volumes. Positive correlations with CR were observed in language, attention, and visual learning in both aMCI and naMCI groups. The current study adds to the minimal literature on CR and naMCI. Results revealed that CR is associated with volumetrics in naMCI only, though cognitive findings were similar in both MCI groups. Possible explanations include heterogeneous disease pathologies, disease stage, or a differential influence of CR on volumetrics in MCI. Additional longitudinal and biomarker studies will better elucidate this relationship.

A deep network-based model of hippocampal memory functions under normal and Alzheimer's disease conditions

We present a deep network-based model of the associative memory functions of the hippocampus. The proposed network architecture has two key modules: (1) an autoencoder module which represents the forward and backward projections of the cortico-hippocampal projections and (2) a module that computes familiarity of the stimulus and implements hill-climbing over the familiarity which represents the dynamics of the loops within the hippocampus. The proposed network is used in two simulation studies. In the first part of the study, the network is used to simulate image pattern completion by autoassociation under normal conditions. In the second part of the study, the proposed network is extended to a heteroassociative memory and is used to simulate picture naming task in normal and Alzheimer's disease (AD) conditions. The network is trained on pictures and names of digits from 0 to 9. The encoder layer of the network is partly damaged to simulate AD conditions. As in case of AD patients, under moderate damage condition, the network recalls superordinate words ("odd" instead of "nine"). Under severe damage conditions, the network shows a null response ("I don't know"). Neurobiological plausibility of the model is extensively discussed.

Structural and functional differences in the brains of patients with MCI with and without depressive symptoms and their relations with Alzheimer's disease: an MRI study

Background

The mild cognitive impairment (MCI) stage among elderly individuals is very complex, and the level of diagnostic accuracy is far from ideal. Some studies have tried to improve the 'MCI due to Alzheimer's disease (AD)' classification by further stratifying these patients into subgroups. Depression-related symptoms may play an important role in helping to better define the MCI stage in elderly individuals.

Objective

In this work, we explored functional and structural differences in the brains of patients with nondepressed MCI (nDMCI) and patients with MCI with depressive symptoms (DMCI), and we examined how these groups relate to AD atrophy patterns and cognitive functioning.

Methods

Sixty-five participants underwent MRI exams and were divided into four groups: cognitively normal, nDMCI, DMCI, and AD. We compared the regional brain volumes, cortical thickness, and white matter microstructure measures using diffusion tensor imaging among groups. Additionally, we evaluated changes in functional connectivity using fMRI data.

Results

In comparison to the nDMCI group, the DMCI patients had more pronounced atrophy in the hippocampus and amygdala. Additionally, DMCI patients had asymmetric damage in the limbic-frontal white matter connection. Furthermore, two medial posterior regions, the isthmus of cingulate gyrus and especially the lingual gyrus, had high importance in the structural and functional differentiation between the two groups.

Conclusion

It is possible to differentiate nDMCI from DMCI patients using MRI techniques, which may contribute to a better characterization of subtypes of the MCI stage.

Volume atrophy in medial temporal cortex and verbal memory scores in American Indians: Data from the Strong Heart Study

INTRODUCTION

Distinguishing Alzheimer's disease (AD) patient subgroups may optimize positive clinical outcomes. Cortical atrophy is correlated with memory deficits, but these associations are understudied in American Indians.

METHODS

We collected imaging and cognition data in the Strong Heart Study (SHS), a cohort of 11 tribes across three regions. We processed 1.5T MRI using FreeSurfer and iterative principal component analysis. Linear mixed models estimated volumetric associations with diabetes.

RESULTS

Over mean 7 years follow-up (N = 818 age 65-89 years), overall volume loss was 0.5% per year. Significant losses associated with diabetes were especially strong in the right hemisphere. Annualized hippocampal, parahippocampal, entorhinal atrophy were worse for men, older age, diabetes, hypertension, stroke; and associated with both encoding and retrieval memory losses.

DISCUSSION

Our findings suggest that diabetes is an important risk factor in American Indians for cortical atrophy and memory loss. Future research should examine opportunities for primary prevention in this underserved population.

Memory Binding Test and Its Associations With Hippocampal Volume Across the Cognitive Continuum Preceding Dementia

Innovative memory paradigms have been introduced to capture subtle memory changes in early Alzheimer's disease (AD). We aimed to examine the associations between different indexes of the challenging Memory Binding Test (MBT) and hippocampal volume (HV) in a sample of individuals with subjective cognitive decline (SCD; n = 50), amnestic mild cognitive impairment (aMCI) due to AD (n = 31), and cognitively normal (CN) older adults (n = 29) recruited from the Czech Brain Aging Study, in contrast to traditional verbal memory tests. Both MBT free and cued recall scores in immediate and delayed recall conditions were associated with lower HV in both SCD and aMCI due to AD, whereas in traditional verbal memory tests only delayed recall scores were associated with lower HV. In SCD, the associations with lower HV in the immediate recall covered specific cued recall indexes only. In conclusion, the MBT is a promising test for detecting subtle hippocampal-associated memory decline during the predementia continuum.

Role of hippocampal subfields in neurodegenerative disease progression analyzed with a multi-scale attention-based network

BACKGROUND AND OBJECTIVE

Both Alzheimer's disease (AD) and Parkinson's disease (PD) are progressive neurodegenerative diseases. Early identification is very important for the prevention and intervention of their progress. Hippocampus plays a crucial role in cognition, in which there are correlations between atrophy of Hippocampal subfields and cognitive impairment in neurodegenerative diseases. Exploring biomarkers in the prediction of early cognitive impairment in AD and PD is significant for understanding the progress of neurodegenerative diseases.

METHODS

A multi-scale attention-based deep learning method is proposed to perform computer-aided diagnosis for neurodegenerative disease based on Hippocampal subfields. First, the two dimensional (2D) Hippocampal Mapping Image (HMI) is constructed and used as input of three branches of the following network. Second, the multi-scale module and attention module are integrated into the 2D residual network to improve the diversity of the extracted features and capture significance of various voxels for classification. Finally, the role of Hippocampal subfields in the progression of different neurodegenerative diseases is analyzed using the proposed method.

RESULTS

Classification experiments between normal control (NC), mild cognitive impairment (MCI), AD, PD with normal cognition (PD-NC) and PD with mild cognitive impairment (PD-MCI) are carried out using the proposed method. Experimental results show that subfields subiculum, presubiculum, CA1, and molecular layer are strongly correlated with cognitive impairment in AD and MCI, subfields GC-DG and fimbria are sensitive in detecting early stage of cognitive impairment in MCI, subfields CA3, CA4, GC-DG, and CA1 show significant atrophy in PD. For exploring the role of Hippocampal subfields in PD cognitive impairment, we find that left parasubiculum, left HATA and left presubiculum could be important biomarkers for predicting conversion from PD-NC to PD-MCI.

CONCLUSION

The proposed multi-scale attention-based network can effectively discover the correlation between subfields and neurodegenerative diseases. Experimental results are consistent with previous clinical studies, which will be useful for further exploring the role of Hippocampal subfields in neurodegenerative disease progression.

Effect of APOE4 Allele and Gender on the Rate of Atrophy in the Hippocampus, Entorhinal Cortex, and Fusiform Gyrus in Alzheimer's Disease

BACKGROUND

The hippocampus, entorhinal cortex, and fusiform gyrus are brain areas that deteriorate during early-stage Alzheimer's disease (AD). The ApoE4 allele has been identified as a risk factor for AD development, is linked to an increase in the aggregation of amyloid ß (Aß) plaques in the brain, and is responsible for atrophy of the hippocampal area. However, to our knowledge, the rate of deterioration over time in individuals with AD, with or without the ApoE4 allele, has not been investigated.

METHOD

In this study, we, for the first time, analyze atrophy in these brain structures in AD patients with and without the ApoE4 using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset.

RESULTS

It was found that the rate of decrease in the volume of these brain areas over 12 months was related to the presence of ApoE4. Further, we found that neural atrophy was not different for female and male patients, unlike prior studies, suggesting that the presence of ApoE4 is not linked to the gender difference in AD.

CONCLUSION

Our results confirm and extend previous findings, showing that the ApoE4 allele gradually impacts brain regions impacted by AD.

An open-source tool for longitudinal whole-brain and white matter lesion segmentation

In this paper we describe and validate a longitudinal method for whole-brain segmentation of longitudinal MRI scans. It builds upon an existing whole-brain segmentation method that can handle multi-contrast data and robustly analyze images with white matter lesions. This method is here extended with subject-specific latent variables that encourage temporal consistency between its segmentation results, enabling it to better track subtle morphological changes in dozens of neuroanatomical structures and white matter lesions. We validate the proposed method on multiple datasets of control subjects and patients suffering from Alzheimer's disease and multiple sclerosis, and compare its results against those obtained with its original cross-sectional formulation and two benchmark longitudinal methods. The results indicate that the method attains a higher test-retest reliability, while being more sensitive to longitudinal disease effect differences between patient groups. An implementation is publicly available as part of the open-source neuroimaging package FreeSurfer.

MC-RVAE: Multi-channel recurrent variational autoencoder for multimodal Alzheimer's disease progression modelling

The progression of neurodegenerative diseases, such as Alzheimer's Disease, is the result of complex mechanisms interacting across multiple spatial and temporal scales. Understanding and predicting the longitudinal course of the disease requires harnessing the variability across different data modalities and time, which is extremely challenging. In this paper, we propose a model based on recurrent variational autoencoders that is able to capture cross-channel interactions between different modalities and model temporal information. These are achieved thanks to its multi-channel architecture and its shared latent variational space, parametrized with a recurrent neural network. We evaluate our model on both synthetic and real longitudinal datasets, the latter including imaging and non-imaging data, with N=897 subjects. Results show that our multi-channel recurrent variational autoencoder outperforms a set of baselines (KNN, random forest, and group factor analysis) for the task of reconstructing missing modalities, reducing the mean absolute error by 5% (w.r.t. the best baseline) for both subcortical volumes and cortical thickness. Our model is robust to missing features within each modality and is able to generate realistic synthetic imaging biomarkers trajectories from cognitive scores.

Evaluating Augmented Reality Landmark Cues and Frame of Reference Displays with Virtual Reality

Daily travel usually demands navigation on foot across a variety of different application domains, including tasks like search and rescue or commuting. Head-mounted augmented reality (AR) displays provide a preview of future navigation systems on foot, but designing them is still an open problem. In this paper, we look at two choices that such AR systems can make for navigation: 1) whether to denote landmarks with AR cues and 2) how to convey navigation instructions. Specifically, instructions can be given via a head-referenced display (screen-fixed frame of reference) or by giving directions fixed to global positions in the world (world-fixed frame of reference). Given limitations with the tracking stability, field of view, and brightness of most currently available head-mounted AR displays for lengthy routes outdoors, we decided to simulate these conditions in virtual reality. In the current study, participants navigated an urban virtual environment and their spatial knowledge acquisition was assessed. We experimented with whether or not landmarks in the environment were cued, as well as how navigation instructions were displayed (i.e., via screen-fixed or world-fixed directions). We found that the world-fixed frame of reference resulted in better spatial learning when there were no landmarks cued; adding AR landmark cues marginally improved spatial learning in the screen-fixed condition. These benefits in learning were also correlated with participants' reported sense of direction. Our findings have implications for the design of future cognition-driven navigation systems.

Three-dimensional anatomical structure formed by granule cell layer and pyramidal cell layer in human hippocampus

In the human hippocampus, the pyramidal layer consists of the inferior aspect of the hippocampus which is organized segmentally. Each segment, together with granule layer of the dentate gyrus, exhibits structural unity. In humans, ellipsoidal protrusions called pyramidal hillocks (PHs), which consist of a thick pyramidal cell layer (PL), are present in the inferior aspect of the hippocampus, and are segmentally organized along a longitudinal axis. It is also known that the granule cell layer (GL) of the dentate gyrus (DG) is not a smooth but undulated structure. However, the cytoarchitectural relationships between the protrusions and undulation have yet to be studied well. Here, we aimed to clarify the three-dimensional cytoarchitecture of the PL and GL of human hippocampus. For that purpose, the GL and PL were three-dimensionally reconstructed from serial sections of human hippocampus stained with hematoxylin and eosin. The GL was shaped as tubing with an opening in the dorsal part, and undulated especially in the medial part, forming digit-like processes. In the base of a digit-like process, protrusions of the GL extended laterally, with longer ones reaching the lateral edge, whereas shorter ones disappeared around the medial 1/3 of the GL. Consequently, the lateral part of the GL was undulated loosely. In the ventral view of the PL, the ellipsoidal PHs were sagittally aligned, whereas in the top view, each PH formed an ellipsoidal trough. Each structural unit was formed by a trough of the PH along the bottom, and had a longer GL protrusion in the upper-center, and shorter GL protrusions located between the longer protrusions and the lateral edge of the GL. A digit-like process extended into a dens. It is concluded that a unit of the PH and the GL comprises the longitudinal segmental formation of the hippocampus.

Hippocampal subfield viscoelasticity in amnestic mild cognitive impairment evaluated with MR elastography

Hippocampal subfields (HCsf) are brain regions important for memory function that are vulnerable to decline with amnestic mild cognitive impairment (aMCI), which is often a preclinical stage of Alzheimer's disease. Studies in aMCI patients often assess HCsf tissue integrity using measures of volume, which has little specificity to microstructure and pathology. We use magnetic resonance elastography (MRE) to examine the viscoelastic mechanical properties of HCsf tissue, which is related to structural integrity, and sensitively detect differences in older adults with aMCI compared to an age-matched control group. Group comparisons revealed HCsf viscoelasticity is differentially affected in aMCI, with CA1-CA2 and DG-CA3 exhibiting lower stiffness and CA1-CA2 exhibiting higher damping ratio, both indicating poorer tissue integrity in aMCI. Including HCsf stiffness in a logistic regression improves classification of aMCI beyond measures of volume alone. Additionally, lower DG-CA3 stiffness predicted aMCI status regardless of DG-CA3 volume. These findings showcase the benefit of using MRE in detecting subtle pathological tissue changes in individuals with aMCI via the HCsf particularly affected in the disease.

Can hippocampal subfield measures supply information that could be used to improve the diagnosis of Alzheimer's disease?

The diagnosis of Alzheimer's disease (AD) needs to be improved. We investigated if hippocampal subfield volume measured by structural imaging, could supply information, so that the diagnosis of AD could be improved. In this study, subjects were classified based on clinical, neuropsychological, and amyloid positivity or negativity using PET scans. Data from 478 elderly Korean subjects grouped as cognitively unimpaired β-amyloid-negative (NC), cognitively unimpaired β-amyloid-positive (aAD), mild cognitively impaired β-amyloid-positive (pAD), mild cognitively impaired-specific variations not due to dementia β-amyloid-negative (CIND), severe cognitive impairment β-amyloid-positive (ADD+) and severe cognitive impairment β-amyloid-negative (ADD-) were used. NC and aAD groups did not show significant volume differences in any subfields. The CIND did not show significant volume differences when compared with either the NC or the aAD (except L-HATA). However, pAD showed significant volume differences in Sub, PrS, ML, Tail, GCMLDG, CA1, CA4, HATA, and CA3 when compared with the NC and aAD. The pAD group also showed significant differences in the hippocampal tail, CA1, CA4, molecular layer, granule cells/molecular layer/dentate gyrus, and CA3 when compared with the CIND group. The ADD- group had significantly larger volumes than the ADD+ group in the bilateral tail, SUB, PrS, and left ML. The results suggest that early amyloid depositions in cognitive normal stages are not accompanied by significant bilateral subfield volume atrophy. There might be intense and accelerated subfield volume atrophy in the later stages associated with the cognitive impairment in the pAD stage, which subsequently could drive the progression to AD dementia. Early subfield volume atrophy associated with the β-amyloid burden may be characterized by more symmetrical atrophy in CA regions than in other subfields. We conclude that the hippocampal subfield volumetric differences from structural imaging show promise for improving the diagnosis of Alzheimer's disease.

Association between cortisol and aging-related hippocampus volume changes in community-dwelling older adults: a 7-year follow-up study

BACKGROUND

Identifying peripheral biomarkers related to modifiable risk factors to prevent dementia at an early stage will be extremely beneficial. We have been studying how older adults can maintain their mental health and continue to live in a familiar community. The aim of this study is to investigate the association between serum cortisol levels and brain volume among older adults in rural Japan.

METHODS

This was a longitudinal study conducted in Kurokawa-cho, Imari, Saga Prefecture, Japan, among people aged 65 years and above, as reported previously. We conducted a survey twice. The first survey was conducted from October 2009 to March 2011 (Timepoint 1) and the second was conducted from November 2016 to September 2017 (Timepoint 2). Blood samples for serum cortisol levels analysis were collected from participants at Timepoint 1. Serum cortisol levels were measured using the enzyme-linked immunosorbent assay. The participants underwent brain MRI examinations, and Mini-Mental State Examination (MMSE) and Clinical Dementia Rating (CDR) for cognitive function assessment at Timepoint 1 and Timepoint 2. We obtained 70 participants (16 men, mean age 72.69 ± 3.18 years; 54 women, mean age 72.69 ± 4.60 years, at Timepoint 1) for analysis. Correlation analysis was performed between serum cortisol levels at baseline (Timepoint 1) and brain volume (Timepoint 1, Timepoint 2, and Timepoint 1-Timepoint 2 difference) using voxel-based morphometry method.

RESULTS

There was no significant difference in serum cortisol levels between men (72.32 ± 17.30 ng/ml) and women (76.60 ± 21.12 ng/ml) at baseline. Additionally, no effect of blood collection time on cortisol levels was observed in these participants. Small volume correction analysis at the cluster level by applying multiple comparison corrections (family-wise error; P < 0.05) showed a negative correlation between serum cortisol levels (Timepoint 1) and brain volume (Timepoint 2) within the region containing the left hippocampus.

CONCLUSIONS

Serum cortisol levels may serve as a peripheral biomarker of age-related volume changes involving the hippocampus in older adults aged 65 years and above.

Altered glymphatic enhancement of cerebrospinal fluid tracer in individuals with chronic poor sleep quality

Chronic sleep disturbance is a risk factor for dementia disease, possibly due to impaired sleep-dependent clearance of toxic metabolic by-products. We compared enrichment of a cerebrospinal fluid (CSF) tracer within brain of patients reporting good or poor sleep quality, assessed by the Pittsburgh Sleep Quality Index (PSQI) questionnaire. Tracer enrichment in a selection of brain regions was assessed using multiphase magnetic resonance imaging up to 48 hours after intrathecal administration of the contrast agent gadobutrol (0.5 ml of 1 mmol/ml) serving as tracer. Tracer enrichment differed between patients with good (PSQI ≤5) and poor (PSQI >5) sleep quality in a cohort of non-dementia individuals (n = 44; age 42.3 ± 14.5 years), and in patients with the dementia subtype idiopathic normal pressure hydrocephalus (n = 24; age 71.0 ± 4.9 years). Sleep impairment was associated with increased CSF tracer enrichment in several brain regions. Cortical brain volume as well as entorhinal cortex thickness was reduced in the oldest cohort and was correlated with the severity of sleep disturbance and the degree of cortical tracer enrichment. We suggest chronic sleep disturbance is accompanied by altered glymphatic function along enlarged perivascular spaces.

Adenosine receptor signalling in Alzheimer’s disease

Alzheimer’s disease (AD) is the most common dementia in the elderly and its increasing prevalence presents treatment challenges. Despite a better understanding of the disease, the current mainstay of treatment cannot modify pathogenesis or effectively address the associated cognitive and memory deficits. Emerging evidence suggests adenosine G protein-coupled receptors (GPCRs) are promising therapeutic targets for Alzheimer’s disease. The adenosine A₁ and A_2A receptors are expressed in the human brain and have a proposed involvement in the pathogenesis of dementia. Targeting these receptors preclinically can mitigate pathogenic β-amyloid and tau neurotoxicity whilst improving cognition and memory. In this review, we provide an accessible summary of the literature on Alzheimer’s disease and the therapeutic potential of A₁ and A_2A receptors. Although there are no available medicines targeting these receptors approved for treating dementia, we provide insights into some novel strategies, including allosterism and the targeting of oligomers, which may increase drug discovery success and enhance the therapeutic response.

CT-Detected MTA Score Related to Disability and Behavior in Older People with Cognitive Impairment

Our study aims to investigate the relationship between medial temporal lobe atrophy (MTA) score, assessed by computed tomography (CT) scans, and functional impairment, cognitive deficit, and psycho-behavioral disorder severity. Overall, 239 (M = 92, F = 147; mean age of 79.3 ± 6.8 years) patients were evaluated with cognitive, neuropsychiatric, affective, and functional assessment scales. MTA was evaluated from 0 (no atrophy) to 4 (severe atrophy). The homocysteine serum was set to two levels: between 0 and 10 µmol/L, and >10 µmol/L. The cholesterol and glycemia blood concentrations were measured. Hypertension and atrial fibrillation presence/absence were collected. A total of 14 patients were MTA 0, 44 patients were MTA 1, 63 patients were MTA 2, 79 patients were MTA 3, and 39 patients were MTA 4. Cognitive (p < 0.0001) and functional (p < 0.0001) parameters decreased according to the MTA severity. According to the diagnosis distribution, AD patient percentages increased by MTA severity (p < 0.0001). In addition, the homocysteine levels increased according to MTA severity (p < 0.0001). Depression (p < 0.0001) and anxiety (p = 0.001) increased according to MTA severity. This study encourages and supports the potential role of MTA score and CT scan in the field of neurodegenerative disorder research and diagnosis.

Intrathecal Contrast-Enhanced Magnetic Resonance Imaging of Cerebrospinal Fluid Dynamics and Glymphatic Enhancement in Idiopathic Normal Pressure Hydrocephalus

Idiopathic normal pressure hydrocephalus (iNPH) is a neurodegenerative disease, characterized by cerebrospinal fluid (CSF) flow disturbance. Today, the only available treatment is CSF diversion surgery (shunt surgery). While traditional imaging biomarkers typically assess CSF space anatomy, recently introduced imaging biomarkers of CSF dynamics and glymphatic enhancement, provide imaging of CSF dynamics and thereby more specifically reveal elements of the underlying pathophysiology. The biomarkers address CSF ventricular reflux grade as well as glymphatic enhancement and derive from intrathecal contrast-enhanced MRI. However, the contrast agent serving as CSF tracer is administered off-label. In medicine, the introduction of new diagnostic or therapeutic methods must consider the balance between risk and benefit. To this end, we performed a prospective observational study of 95 patients with iNPH, comparing different intrathecal doses of the MRI contrast agent gadobutrol (0.10, 0.25, and 0.50 mmol, respectively), aiming at the lowest reasonable dose needed to retrieve diagnostic information about the novel MRI biomarkers. The present observations disclosed a dose-dependent enrichment of subarachnoid CSF spaces (cisterna magna, vertex, and velum interpositum) with dose-dependent ventricular reflux of tracer in iNPH, as well as dose-dependent glymphatic tracer enrichment. The association between tracer enrichment in CSF and parenchymal compartments were as well dose-related. Intrathecal gadobutrol in a dose of 0.25 mmol, but not 0.10 mmol, was at 1.5T MRI considered sufficient for imaging altered CSF dynamics and glymphatic enhancement in iNPH, even though 3T MRI provided better sensitivity. Tracer enrichment in CSF at the vertex and within the cerebral cortex and subcortical white matter was deemed too low for maintaining diagnostic information from a dose of 0.10 mmol. We conclude that reducing the intrathecal dose of gadobutrol from 0.50 to 0.25 mmol gadobutrol improves the safety margin while maintaining the necessary diagnostic information about disturbed CSF homeostasis and glymphatic failure in iNPH.

Volume of the posterior hippocampus mediates age-related differences in spatial context memory and is correlated with increased activity in lateral frontal, parietal and occipital regions in healthy aging

Healthy aging is associated with episodic memory decline, particularly in the ability to encode and retrieve object-context associations (context memory). Neuropsychological and neuroimaging studies have highlighted the importance of the medial temporal lobes (MTL) in supporting episodic memory across the lifespan. However, given the functional heterogeneity of the MTL, volumetric declines in distinct regions may impact performance on specific episodic memory tasks, and affect the function of the large-scale neurocognitive networks supporting episodic memory encoding and retrieval. In the current study, we investigated how MTL structure may mediate age-related differences in performance on spatial and temporal context memory tasks, in a sample of 125 healthy adults aged 19-76 years old. Standard T1-weighted MRIs were segmented into the perirhinal, entorhinal and parahippocampal cortices, as well as the anterior and posterior hippocampal subregions. We observed negative linear and quadratic associations between age and volume of the parahippocampal cortex, and anterior and posterior hippocampal subregions. We also found that volume of the posterior hippocampus fully mediated the association between age and spatial, but not temporal context memory performance. Further, we employed a multivariate behavior partial-least-squares analysis to assess how age and regional MTL volumes correlated with brain activity during the encoding and retrieval of spatial context memories. We found that greater activity within lateral prefrontal, parietal, and occipital regions, as well as within the anterior MTL was related to older age and smaller volume of the posterior hippocampus. Our results highlight the heterogeneity of MTL contributions to episodic memory across the lifespan and provide support for the posterior-anterior shift in aging, and scaffolding theory of aging and cognition.

Circulating Lipocalin-2 level is positively associated with cognitive impairment in patients with metabolic syndrome

The association between Lipocalin-2 (LCN2) and cognition in patients with metabolic syndrome (MetS) has not been thoroughly investigated. We aimed to evaluate whether serum LCN2 levels are associated with the alteration of cognitive function in patients with MetS. The total of 191 non-demented participants with MetS were enrolled onto the study in 2015, and a cohort study was conducted in a subpopulation in 2020. After adjustment for sex, age, waist circumference, creatinine levels, and HbA1C, an association between the higher serum LCN2 levels and the lower Montreal cognitive assessment (MoCA) scores was observed (B = − 0.045; 95%CI − 0.087, − 0.004; p 0.030). A total of 30 participants were followed-up in 2020. Serum LCN2 levels were decreased in correlation with age (23.31 ± 12.32 ng/ml in 2015 and 15.98 ± 11.28 ng/ml in 2020, p 0.024), while other metabolic parameters were unchanged. Magnetic resonance imaging studies were conducted on a subsample of patients in 2020 (n = 15). Associations between high serum LCN2 levels from 2015 and 2020 and changes in brain volume of hippocampus and prefrontal cortex from 2020 have been observed. These findings suggest a relationship between changes of the level of circulating LCN2, cognitive impairment, and changes in brain volume in patients with MetS. However, further investigation is still needed to explore the direct effect of circulating LCN2 on the cognition of MetS patients.

The Comparative Effectiveness of Traditional Chinese Medicine Exercise Therapies in Elderly People With Mild Cognitive Impairment: A Systematic Review and Network Meta-Analysis

Background

Mild cognitive impairment (MCI) in the elderly is a health problem worldwide. Studies have confirmed that traditional Chinese medicine (TCM) exercise therapies can improve MCI. However, which therapy is the best and their impacts on brain function remain controversial and uncertain. This study aims to compare and rank TCM exercise therapies for MCI in the elderly, and analyze their effects on brain function, in order to find an optimal intervention and provide a basis for clinical treatments decision-making.

Methods

The Web of Science, PubMed, EMBASE, Cochrane Central Register of Controlled Trials, Clinical Trials, China National Knowledge Infrastructure (CNKI), Wangfang database, China Science and Technology Journal Database, and Chinese Biomedical Medicine (CBM) were searched through October 28, 2021. Two researchers reviewed all the studies and extracted the data. The ADDIS software version 1.16.8 and the Bayesian hierarchical model were used for pair-wise meta-analysis and network meta-analysis, and the STATA software version 14.0 was used to draw the network evidence plots and funnel plots.

Results

A total of 23 studies on 2282 participants were included in this study. In the pair-wise meta-analysis, TCM exercise therapies (Baduanjin exercise, Tai Chi, Liuzijue exercise and finger exercise) were superior to non-TCM exercise therapies (stretching and toning exercise, usual care, health education and routine daily activities) in terms of MMSE, MoCA and ADL outcomes. In the network meta-analysis, the MMSE outcome ranked Baduanjin exercise (78%) as the best intervention and Tai Chi (36%) as the second. The MoCA outcome ranked Baduanjin exercise (62%) as the best intervention. For the ADL outcome, Baduanjin exercise (60%) ranked the best, and followed by finger exercise (43%).

Conclusion

TCM exercise therapies may improve the cognitive function in elderly patients with MCI. Among the four therapies included, the Baduanjin exercise may be the preferred therapy for MCI in the elderly, and its mechanism may be related to the regulation of cognitive-related brain function and structure.

Systematic Review Registration

https://inplasy.com, identifier: INPLASY202070006.

Cannabis Use and Resting State Functional Connectivity in the Aging Brain

Several lines of evidence suggest that older adults (aged 65+) sharply increased their cannabis use over the last decade, highlighting a need to understand the effects of cannabis in this age group. Pre-clinical models suggest that cannabinoids affect the brain and cognition in an age-dependent fashion, having generally beneficial effects on older animals and deleterious effects on younger ones. However, there is little research on how cannabis affects the brains of older adults or how older adults differ from younger adults who use cannabis. Resting state functional connectivity (rsFC) measures provide sensitive metrics of age-related cognitive decline. Here we compared rsFC in older adults who are either regular users of cannabis or non-users. We found stronger connectivity between sources in the hippocampus and parahippocampal cortex, and targets in the anterior lobes of the cerebellum in older adult cannabis users relative to non-users. A similar pattern of strengthened connectivity between hippocampal and cerebellar structures was also present in 25-35 year old non-users in comparison to 60-88 year old non-users. These findings suggest that future studies should examine both the potential risks of cannabinoids, as well as a potential benefits, on cognition and brain health for older adults.

Loss of corneal nerves and brain volume in mild cognitive impairment and dementia

Introduction

This study compared the capability of corneal confocal microscopy (CCM) with magnetic resonance imaging (MRI) brain volumetry for the diagnosis of mild cognitive impairment (MCI) and dementia.

Methods

In this cross‐sectional study, participants with no cognitive impairment (NCI), MCI, and dementia underwent assessment of Montreal Cognitive Assessment (MoCA), MRI brain volumetry, and CCM.

Results

Two hundred eight participants with NCI (n = 42), MCI (n = 98), and dementia (n = 68) of comparable age and gender were studied. For MCI, the area under the curve (AUC) of CCM (76% to 81%), was higher than brain volumetry (52% to 70%). For dementia, the AUC of CCM (77% to 85%), was comparable to brain volumetry (69% to 93%). Corneal nerve fiber density, length, branch density, whole brain, hippocampus, cortical gray matter, thalamus, amygdala, and ventricle volumes were associated with cognitive impairment after adjustment for confounders (All P’s < .01).

Discussion

The diagnostic capability of CCM compared to brain volumetry is higher for identifying MCI and comparable for dementia, and abnormalities in both modalities are associated with cognitive impairment.

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.

Leisure Activity Variety and Brain Volume Among Community-Dwelling Older Adults: Analysis of the Neuron to Environmental Impact Across Generations Study Data

Background: Recent findings indicate that leisure activity (LA) delays cognitive decline and reduces the risk of dementia. However, the association between LA and brain volume remains unclear. This study aimed to examine the association between LA variety and brain volume with a focus on the hippocampus and gray matter. Methods: Data were obtained from the baseline survey of the Neuron to Environmental Impact across Generations study, which had targeted community-dwelling older adults living in Niigata, Japan. We divided LAs into 10 categories, and counted the number of categories of activities in which the participants engaged. We classified them as follows: 0 (i.e., no activity), 1, 2, or ≥ 3 types. Brain volume was assessed through magnetic resonance imaging, and hippocampal and gray matter volumes were ascertained. Results: The sample size was 482. Multiple linear regression analysis showed that hippocampal and gray matter volumes were significantly greater among participants with ≥ 3 types of LAs than among their no-activity counterparts. Hippocampal volume was significantly greater among those who engaged in one type of LA than among those who engaged in no such activity. Sex-stratified analysis revealed that hippocampal volumes were significantly greater among males who engaged in ≥ 3 types of LAs and one type of LA. However, no such association was found among females. Conclusion: The present findings suggest that engaging in a wide range of LAs is related to hippocampal and gray matter volumes. Furthermore, there was a sex difference in the association between LA variety and brain volume.

Regional Brain Volume, Brain Reserve and MMSE Performance in Healthy Aging From the NEUROAGE Cohort: Contributions of Sex, Education, and Depression Symptoms

Objective: The aim of this study was twofold. First, to investigate the relationship between age, gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) volumes, brain reserve (BR), and specific regions of interest (ROIs) with global cognitive function in healthy older adults participating in a longitudinal study on aging in the island country of Cyprus. Second, to assess the contribution of important demographic and psychosocial factors on brain volume. Specifically, the effects of sex and years of education and the association between depression symptoms on brain volume were also explored in this Mediterranean cohort.

Methods: Eighty-seven healthy older adults (males = 37, females = 50) scoring ≥24 on the Mini-Mental State Examination (MMSE) were included, with a mean age of 72.75 years and a mean educational level of 10.48 years. The Geriatric Depression Scale was used to assess depression. T1-weighted magnetic resonance images were used to calculate global and regional volumes.

Results: Age was negatively correlated with GM, WM, BR, MMSE scores, and ROIs, including the hippocampus, amygdala, entorhinal cortex, prefrontal cortex, anterior cingulate gyrus, and positively with CSF. Higher MMSE scores positively correlated with GM volume. Women exhibited greater levels of depression than men. Depression was also negatively correlated with GM volume and MMSE scores. Men had greater ventricular size than women and participants with higher education had greater ventricular expansion than those with fewer years in education.

Conclusions: The reported structural changes provide evidence on the overlap between age-related brain changes and healthy cognitive aging and suggest that these age changes affect certain regions. Furthermore, sex, depressive symptomatology, and education are significant predictors of the aging brain. Brain reserve and higher education accommodate these changes and works against the development of clinical symptoms.

Acupuncture for amnestic mild cognitive impairment: A pilot multicenter, randomized, parallel controlled trial

INTRODUCTION

Patients with amnesic mild cognitive impairment (aMCI) are more likely to develop Alzheimer disease than corresponding age normal population. Because Alzheimer disease is irreversible, early intervention for aMCI patients seems important and urgent. We have designed a pilot multicenter, randomized, parallel controlled trial to assess the efficacy and safety of acupuncture on aMCI, explore the feasibility of acupuncture in the treatment of aMCI, so as to provide a reference for large-sample clinical trials in the next stage.

METHOD

We designed a pilot multicenter, randomized, parallel controlled trial. This trial aims to test the feasibility of carrying out a large-sample clinical trial. In this trial, 50 eligible patients with aMCI will be included and allocated to acupuncture group (n = 25) or sham acupuncture group (n = 25) at random. Subjects will accept treatment 2 times a week for 12 weeks continuously, with a total of 24 treatment sessions. We will select 6 acupoints (GV20, GV14, bilateral BL18, bilateral BL23). For the clinical outcomes, the primary outcome is Montreal cognitive assessment, which will be assessed from baseline to the end of this trial. And the secondary outcomes are Mini-mental State Examination, Delayed Story Recall, Clinical Dementia Rating scale, Global Deterioration Scale, Activity of Daily Life, Alzheimer Disease Assessment Scale-Cognitive Section, brain magnetic resonance imaging, brain functional magnetic resonance imaging, and event-related potential P300, which will be assessed before and after treatment. In addition, we will assess the safety outcomes from baseline to the end of this trial and feasibility outcome after treatment. We will evaluate neuropsychological assessment scale (Montreal cognitive assessment, Mini-mental State Examination, Alzheimer Disease Assessment Scale-Cognitive Section) at 3 months and 6 months after treatment.

DISCUSSION

This pilot trial aims to explore the feasibility of the trial, verify essential information of its efficacy and safety. This pilot study will provide a preliminary basis for carrying out a larger clinical trial of acupuncture on aMCI in near future.

Medial Temporal Lobe Subregional Atrophy in Aging and Alzheimer's Disease: A Longitudinal Study

Medial temporal lobe (MTL) atrophy is a key feature of Alzheimer's disease (AD), however, it also occurs in typical aging. To enhance the clinical utility of this biomarker, we need to better understand the differential effects of age and AD by encompassing the full AD-continuum from cognitively unimpaired (CU) to dementia, including all MTL subregions with up-to-date approaches and using longitudinal designs to assess atrophy more sensitively. Age-related trajectories were estimated using the best-fitted polynomials in 209 CU adults (aged 19–85). Changes related to AD were investigated among amyloid-negative (Aβ−) (n = 46) and amyloid-positive (Aβ+) (n = 14) CU, Aβ+ patients with mild cognitive impairment (MCI) (n = 33) and AD (n = 31). Nineteen MCI-to-AD converters were also compared with 34 non-converters. Relationships with cognitive functioning were evaluated in 63 Aβ+ MCI and AD patients. All participants were followed up to 47 months. MTL subregions, namely, the anterior and posterior hippocampus (aHPC/pHPC), entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36 [as perirhinal cortex (PRC) substructures], and parahippocampal cortex (PHC), were segmented from a T1-weighted MRI using a new longitudinal pipeline (LASHiS). Statistical analyses were performed using mixed models. Adult lifespan models highlighted both linear (PRC, BA35, BA36, PHC) and nonlinear (HPC, aHPC, pHPC, ERC) trajectories. Group comparisons showed reduced baseline volumes and steeper volume declines over time for most of the MTL subregions in Aβ+ MCI and AD patients compared to Aβ− CU, but no differences between Aβ− and Aβ+ CU or between Aβ+ MCI and AD patients (except in ERC). Over time, MCI-to-AD converters exhibited a greater volume decline than non-converters in HPC, aHPC, and pHPC. Most of the MTL subregions were related to episodic memory performances but not to executive functioning or speed processing. Overall, these results emphasize the benefits of studying MTL subregions to distinguish age-related changes from AD. Interestingly, MTL subregions are unequally vulnerable to aging, and those displaying non-linear age-trajectories, while not damaged in preclinical AD (Aβ+ CU), were particularly affected from the prodromal stage (Aβ+ MCI). This volume decline in hippocampal substructures might also provide information regarding the conversion from MCI to AD-dementia. All together, these findings provide new insights into MTL alterations, which are crucial for AD-biomarkers definition.

Corneal Nerve and Brain Imaging in Mild Cognitive Impairment and Dementia

Background:

Visual rating of medial temporal lobe atrophy (MTA) is an accepted structural neuroimaging marker of Alzheimer’s disease. Corneal confocal microscopy (CCM) is a non-invasive ophthalmic technique that detects neuronal loss in peripheral and central neurodegenerative disorders.

Objective:

To determine the diagnostic accuracy of CCM for mild cognitive impairment (MCI) and dementia compared to medial temporal lobe atrophy (MTA) rating on MRI.

Methods:

Subjects aged 60–85 with no cognitive impairment (NCI), MCI, and dementia based on the ICD-10 criteria were recruited. Subjects underwent cognitive screening, CCM, and MTA rating on MRI.

Results:

182 subjects with NCI (n = 36), MCI (n = 80), and dementia (n = 66), including AD (n = 19, 28.8%), VaD (n = 13, 19.7%), and mixed AD (n = 34, 51.5%) were studied. CCM showed a progressive reduction in corneal nerve fiber density (CNFD, fibers/mm²) (32.0±7.5 versus 24.5±9.6 and 20.8±9.3, p < 0.0001), branch density (CNBD, branches/mm²) (90.9±46.5 versus 59.3±35.7 and 53.9±38.7, p < 0.0001), and fiber length (CNFL, mm/mm²) (22.9±6.1 versus 17.2±6.5 and 15.8±7.4, p < 0.0001) in subjects with MCI and dementia compared to NCI. The area under the ROC curve (95% CI) for the diagnostic accuracy of CNFD, CNBD, CNFL compared to MTA-right and MTA-left for MCI was 78% (67–90%), 82% (72–92%), 86% (77–95%) versus 53% (36–69%) and 40% (25–55%), respectively, and for dementia it was 85% (76–94%), 84% (75–93%), 85% (76–94%) versus 86% (76–96%) and 82% (72–92%), respectively.

Conclusion:

The diagnostic accuracy of CCM, a non-invasive ophthalmic biomarker of neurodegeneration, was high and comparable with MTA rating for dementia but was superior to MTA rating for MCI.