Patterns of Cerebellar Gray Matter Atrophy Across Alzheimer's Disease Progression

Cerebellum in Alzheimer's disease and other neurodegenerative diseases: an emerging research frontier

The cerebellum is crucial for both motor and nonmotor functions. Alzheimer's disease (AD), alongside other dementias such as vascular dementia (VaD), Lewy body dementia (DLB), and frontotemporal dementia (FTD), as well as other neurodegenerative diseases (NDs) like Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), Huntington's disease (HD), and spinocerebellar ataxias (SCA), are characterized by specific and non-specific neurodegenerations in central nervous system. Previously, the cerebellum's significance in these conditions was underestimated. However, advancing research has elevated its profile as a critical node in disease pathology. We comprehensively review the existing evidence to elucidate the relationship between cerebellum and the aforementioned diseases. Our findings reveal a growing body of research unequivocally establishing a link between the cerebellum and AD, other forms of dementia, and other NDs, supported by clinical evidence, pathological and biochemical profiles, structural and functional neuroimaging data, and electrophysiological findings. By contrasting cerebellar observations with those from the cerebral cortex and hippocampus, we highlight the cerebellum's distinct role in the disease processes. Furthermore, we also explore the emerging therapeutic potential of targeting cerebellum for the treatment of these diseases. This review underscores the importance of the cerebellum in these diseases, offering new insights into the disease mechanisms and novel therapeutic strategies.

Cerebello-Hippocampal Interactions in the Human Brain: A New Pathway for Insights Into Aging

The cerebellum is recognized as being important for optimal behavioral performance across task domains, including motor function, cognition, and affect. Decades of work have highlighted cerebello-thalamo-cortical circuits, from both structural and functional perspectives. However, these circuits of interest have been primarily (though not exclusively) focused on targets in the cerebral cortex. In addition to these cortical connections, the circuit linking the cerebellum and hippocampus is of particular interest. Recently, there has been an increased interest in this circuit, thanks in large part to novel findings in the animal literature demonstrating that neuronal firing in the cerebellum impacts that in the hippocampus. Work in the human brain has provided evidence for interactions between the cerebellum and hippocampus, though primarily this has been in the context of spatial navigation. Given the role of both regions in cognition and aging, and emerging evidence indicating that the cerebellum is impacted in age-related neurodegenerative disease such as Alzheimer's, I propose that further attention to this circuit is warranted. Here, I provide an overview of cerebello-hippocampal interactions in animal models and from human imaging and outline the possible utility of further investigations to improve our understanding of aging and age-related cognitive decline.

Digging into the intrinsic capacity concept: Can it be applied to Alzheimer's disease?

Historically, aging research has largely centered on disease pathology rather than promoting healthy aging. The World Health Organization's (WHO) policy framework (2015-2030) underscores the significance of fostering the contributions of older individuals to their families, communities, and economies. The WHO has introduced the concept of intrinsic capacity (IC) as a key metric for healthy aging, encompassing five primary domains: locomotion, vitality, sensory, cognitive, and psychological. Past AD research, constrained by methodological limitations, has focused on single outcome measures, sidelining the complexity of the disease. Our current scientific milieu, however, is primed to adopt the IC concept. This is due to three critical considerations: (I) the decline in IC is linked to neurocognitive disorders, including AD, (II) cognition, a key component of IC, is deeply affected in AD, and (III) the cognitive decline associated with AD involves multiple factors and pathophysiological pathways. Our study explores the application of the IC concept to AD patients, offering a comprehensive model that could revolutionize the disease's diagnosis and prognosis. There is a dearth of information on the biological characteristics of IC, which are a result of complex interactions within biological systems. Employing a systems biology approach, integrating omics technologies, could aid in unraveling these interactions and understanding IC from a holistic viewpoint. This comprehensive analysis of IC could be leveraged in clinical settings, equipping healthcare providers to assess AD patients' health status more effectively and devise personalized therapeutic interventions in accordance with the precision medicine paradigm. We aimed to determine whether the IC concept could be extended from older individuals to patients with AD, thereby presenting a model that could significantly enhance the diagnosis and prognosis of this disease.

Pathology-specific patterns of cerebellar atrophy in neurodegenerative disorders

INTRODUCTION

Associations of cerebellar atrophy with specific neuropathologies in Alzheimer's disease and related dementias (ADRD) have not been systematically analyzed. This study examined cerebellar gray matter volume across major pathological subtypes of ADRD.

METHODS

Cerebellar gray matter volume was examined using voxel-based morphometry in 309 autopsy-proven ADRD cases and 80 healthy controls. ADRD subtypes included AD, mixed Lewy body disease and AD (LBD-AD), and frontotemporal lobar degeneration (FTLD). Clinical function was assessed using the Clinical Dementia Rating (CDR) scale.

RESULTS

Distinct patterns of cerebellar atrophy were observed in all ADRD subtypes. Significant cerebellar gray matter changes appeared in the early stages of most subtypes and the very early stages of AD, LBD-AD, FTLD-TDP type A, and progressive supranuclear palsy. Cortical atrophy positively predicted cerebellar atrophy across all subtypes.

DISCUSSION

Our findings establish pathology-specific profiles of cerebellar atrophy in ADRD and propose cerebellar neuroimaging as a non-invasive biomarker for differential diagnosis and disease monitoring.

HIGHLIGHTS

Cerebellar atrophy was examined in 309 patients with autopsy-proven neurodegeneration. Distinct patterns of cerebellar atrophy are found in all pathological subtypes of Alzheimer's disease and related dementias (ADRD). Cerebellar atrophy is seen in early-stage (Clinical Dementia Rating [CDR] ≤1) AD, Lewy body dementia (LBD), frontotemporal lobar degeneration with tau-positive inclusion (FTLD-tau), and FTLD-transactive response DNA binding protein (FTLD-TDP). Cortical atrophy positively predicts cerebellar atrophy across all neuropathologies.

Functional Connectivity Differences in Distinct Dentato-Cortical Networks in Alzheimer's Disease and Mild Cognitive Impairment

Recent research has implicated the cerebellum in Alzheimer's disease (AD), and cerebrocerebellar network connectivity is emerging as a possible contributor to symptom severity. The cerebellar dentate nucleus (DN) has parallel motor and non-motor sub-regions that project to motor and frontal regions of the cerebral cortex, respectively. These distinct dentato-cortical networks have been delineated in the non-human primate and human brain. Importantly, cerebellar regions prone to atrophy in AD are functionally connected to atrophied regions of the cerebral cortex, suggesting that dysfunction perhaps occurs at a network level. Investigating functional connectivity (FC) alterations of the DN is a crucial step in understanding the cerebellum in AD and in mild cognitive impairment (MCI). Inclusion of this latter group stands to provide insights into cerebellar contributions prior to diagnosis of AD. The present study investigated FC differences in dorsal (dDN) and ventral (vDN) DN networks in MCI and AD relative to cognitively normal participants (CN) and relationships between FC and behavior. Our results showed patterns indicating both higher and lower functional connectivity in both dDN and vDN in AD compared to CN. However, connectivity in the AD group was lower when compared to MCI. We argue that these findings suggest that the patterns of higher FC in AD may act as a compensatory mechanism. Additionally, we found associations between the individual networks and behavior. There were significant interactions between dDN connectivity and motor symptoms. However, both DN seeds were associated with cognitive task performance. Together, these results indicate that cerebellar DN networks are impacted in AD, and this may impact behavior. In concert with the growing body of literature implicating the cerebellum in AD, our work further underscores the importance of investigations of this region. We speculate that much like in psychiatric diseases such as schizophrenia, cerebellar dysfunction results in negative impacts on thought and the organization therein. Further, this is consistent with recent arguments that the cerebellum provides crucial scaffolding for cognitive function in aging. Together, our findings stand to inform future clinical work in the diagnosis and understanding of this disease.

Cognitive impairment associated with cerebellar volume loss in spinocerebellar ataxia type 3

BACKGROUND

Many neuroscience and neurology studies have forced a reconsideration of the traditional motor-related scope of cerebellar function, which has now expanded to include various cognitive functions. Spinocerebellar ataxia type 3 (SCA3; the most common hereditary ataxia) is neuropathologically characterized by cerebellar atrophy and frequently presents with cognitive impairment.

OBJECTIVE

To characterize cognitive impairment in SCA3 and investigate the cerebellum-cognition associations.

METHODS

This prospective, cross-sectional cohort study recruited 126 SCA3 patients and 41 healthy control individuals (HCs). Participants underwent a brain 3D T1-weighted images as well as neuropsychological tests. Voxel-based morphometry (VBM) and region of interest (ROI) approaches were performed on the 3D T1-weighted images. CERES was used to automatically segment cerebellums. Patients were grouped into cognitively impaired (CI) and cognitively preserved (CP), and clinical and MRI parameters were compared. Multivariable regression models were fitted to examine associations between cerebellar microstructural alterations and cognitive domain impairments.

RESULTS

Compared to HCs, SCA3 patients showed cognitive domain impairments in information processing speed, verbal memory, executive function, and visuospatial perception. Between CI and CP subgroups, the CI subgroup was older and had lower education, as well as higher severity scores. VBM and ROI analyses revealed volume loss in cerebellar bilateral lobule VI, right lobule Crus I, and right lobule IV of the CI subgroup, and all these cerebellar lobules were associated with the above cognitive domain impairments.

CONCLUSIONS

Our findings demonstrate the multiple cognitive domain impairments in SCA3 patients and indicate the responsible cerebellar lobules for the impaired cognitive domain(s).

Alterations in Gray Matter Structural Networks in Amnestic Mild Cognitive Impairment: A Source-Based Morphometry Study

Background

Amnestic mild cognitive impairment (aMCI), considered as the prodromal stage of Alzheimer's disease, is characterized by isolated memory impairment and cerebral gray matter volume (GMV) alterations. Previous structural MRI studies in aMCI have been mainly based on univariate statistics using voxel-based morphometry.

Objective

We investigated structural network differences between aMCI patients and cognitively normal older adults by using source-based morphometry, a multivariate approach that considers the relationship between voxels of various parts of the brain.

Methods

Ninety-one aMCI patients and 80 cognitively normal controls underwent structural MRI and neuropsychological assessment. Spatially independent components (ICs) that covaried between participants were estimated and a multivariate analysis of covariance was performed with ICs as dependent variables, diagnosis as independent variable, and age, sex, education level, and site as covariates.

Results

aMCI patients exhibited reduced GMV in the precentral, temporo-cerebellar, frontal, and temporal network, and increased GMV in the left superior parietal network compared to controls (pFWER < 0.05, Holm-Bonferroni correction). Moreover, we found that diagnosis, more specifically aMCI, moderated the positive relationship between occipital network and Mini-Mental State Examination scores (pFWER < 0.05, Holm-Bonferroni correction).

Conclusions

Our results showed GMV alterations in temporo-fronto-parieto-cerebellar networks in aMCI, extending previous results obtained with univariate approaches.

New Frontiers for the Understanding of Aging: The Power and Possibilities of Studying the Cerebellum

Understanding behavior in aging has benefited greatly from cognitive neuroscience. Our foundational understanding of the brain in advanced age is based on what now amounts to several decades of work demonstrating differences in brain structure, network organization, and function. Earlier work in this field was focused primarily on the prefrontal cortex and hippocampus. More recent evidence has expanded our understanding of the aging brain to also implicate the cerebellum. Recent frameworks have suggested that the cerebellum may act as scaffolding for cortical function, and there is an emerging literature implicating the structure in Alzheimer's disease. At this juncture, there is evidence highlighting the potential importance of the cerebellum in advanced age, though the field of study is relatively nascent. Here, we provide an overview of key findings in the literature as it stands now and highlight several key future directions for study with respect to the cerebellum in aging.

Sleep deprivation aggravated amyloid β oligomers-induced damage to the cerebellum of rats: Evidence from magnetic resonance imaging

For quite a long time, researches on Alzheimer's disease (AD) primarily focused on the cortex and hippocampus, while the cerebellum has been ignored because of its abnormalities considered to appear in the late stage of AD. In recent years, increasing evidence suggest that the cerebellar pathological changes possibly occur in the preclinical phase of AD, which is also associated with sleep disorder. Sleep disturbance is a high risk factor of AD. However, the changes and roles of cerebellum has rarely been reported under conditions of AD accompanied with sleep disorders. In this study, using an amyloid-β oligomers (AβO)-induced rat model of AD subjected to sleep deprivation, combining with a 7.0 T animals structural magnetic resonance imaging (MRI), we assessed structural changes of cerebellum in MRI. Our results showed that sleep deprivation combined with AβO led to an increased FA value in the anterior lobe of cerebellum, decreased ADC value in the cerebellar lobes and cerebellar nuclei, and increased cerebellum volume. Besides that, sleep deprivation exacerbated the damage of AβO to the cerebellar structural network. This study demonstrated that sleep deprivation could aggravate the damage to cerebellum induced by AβO. The present findings provide supporting evidence for the involvement of cerebellum in the early pathology of AD and sleep loss. Our data would contribute to advancing the understanding of the mysterious role of cerebellum in AD and sleep disorders, as well as would be helpful for developing non-invasive MRI biomarkers for screening early AD patients with self-reported sleep disturbances.

The electrophysiological and neuropathological profiles of cerebellum in APPswe /PS1ΔE9 mice: A hypothesis on the role of cerebellum in Alzheimer's disease

We propose the hypothesis that the cerebellar electrophysiology and sleep-wake cycles may be altered at the early stage of Alzheimer's disease (AD), proceeding the amyloid-β neuropathological hallmarks. The electrophysiologic characteristics of cerebellum thereby might be served as a biomarker in the prepathological detection of AD. Sleep disturbances are common in preclinical AD patients, and the cerebellum has been implicated in sleep-wake regulation by several pioneer studies. Additionally, recent studies suggest that the structure and function of the cerebellum may be altered at the early stages of AD, indicating that the cerebellum may be involved in the disease's progression. We used APPswe /PS1ΔE9 mice as a model of AD, monitored and analyzed electroencephalogram data, and assessed neuropathological profiles in the cerebellum of AD mice. Our hypothesis may establish a linkage between the cerebellum and AD, thereby potentially providing new perspectives on the pathogenesis of the disease.

Estimating uncertainty in read-out patterns: Application to controls-based denoising and voxel-based morphometry patterns in neurodegenerative and neuropsychiatric diseases

Quantifying pathology-related patterns in patient data with pattern expression score (PES) is a standard approach in medical image analysis. In order to estimate the PES error, we here propose to express the uncertainty contained in read-out patterns in terms of the expected squared Euclidean distance between the read-out pattern and the unknown "true" pattern (squared standard error of the read-out pattern, SE2 ). Using SE2 , we predicted and optimized the net benefit (NBe) of the recently suggested method controls-based denoising (CODE) by weighting patterns of nonpathological variance (NPV). Multi-center MRI (1192 patients with various neurodegenerative and neuropsychiatric diseases, 1832 healthy controls) were analysed with voxel-based morphometry. For each pathology, accounting for SE2 , NBe correctly predicted classification improvement and allowed to optimize NPV pattern weights. Using these weights, CODE improved classification performances in all but one analyses, for example, for prediction of conversion to Alzheimer's disease (AUC 0.81 vs. 0.75, p = .01), diagnosis of autism (AUC 0.66 vs. 0.60, p < .001), and of major depressive disorder (AUC 0.62 vs. 0.50, p = .03). We conclude that the degree of uncertainty in a read-out pattern should generally be reported in PES-based analyses and suggest using weighted CODE as a complement to PES-based analyses.

New prospects on cerebellar reserve: Remarks on neuroprotective effects of experience in animals and humans

The ability of the brain to change structure and function in response to experience accounts for its ability to successfully adapt to the environment in both learning processes and unique phases, such as during development and repair. On this basis, the occurrence of the brain, cognitive, and neural reserves has been advanced to explain the discrepancies between the extent of neurological damage and the severity of clinical manifestations described in patients with different life span experiences. Research on this topic highlighted the neuroprotective role of complex stimulations, allowing the brain to better cope with the damage. This framework was initially developed by observing patients with Alzheimer's disease, and it has since been progressively expanded to multifarious pathological states. The cerebellum is known to be particularly responsive to experience through extensive plastic rearrangements. The neuroprotective value exerted by reserve mechanisms appears to be suitable for basic neuronal plasticity in the cerebellum. Thus, it is of primary interest to deepen our understanding of how life experiences modify individuals' cerebellar morphology and functionality. The present study is aimed at analyzing the evidence provided on this topic by animal and human studies. For animals, we considered the studies in which subjects were submitted to enhanced stimulations before the damage occurred. For humans, we considered studies in which previous lifelong high-level experiences were associated with superior cerebellar abilities to cope with injury. Detailed indications of the processes underlying cerebellar reserves may be important in proposing effective interventions for patients suffering from pathologies that directly or indirectly damage cerebellar functionality.

Disrupted Balance of Gray Matter Volume and Directed Functional Connectivity in Mild Cognitive Impairment and Alzheimer's Disease

BACKGROUND

Alterations in functional connectivity have been demonstrated in Alzheimer's disease (AD), an age-progressive neurodegenerative disorder that affects cognitive function; however, directional information flow has never been analyzed.

OBJECTIVE

This study aimed to determine changes in resting-state directional functional connectivity measured using a novel approach, granger causality density (GCD), in patients with AD, and mild cognitive impairment (MCI) and explore novel neuroimaging biomarkers for cognitive decline detection.

METHODS

In this study, structural MRI, resting-state functional magnetic resonance imaging, and neuropsychological data of 48 Alzheimer's Disease Neuroimaging Initiative participants were analyzed, comprising 16 patients with AD, 16 with MCI, and 16 normal controls. Volume-based morphometry (VBM) and GCD were used to calculate the voxel-based gray matter (GM) volumes and directed functional connectivity of the brain. We made full use of voxel-based between-group comparisons of VBM and GCD values to identify specific regions with significant alterations. In addition, Pearson's correlation analysis was conducted between directed functional connectivity and several clinical variables. Furthermore, receiver operating characteristic (ROC) analysis related to classification was performed in combination with VBM and GCD.

RESULTS

In patients with cognitive decline, abnormal VBM and GCD (involving inflow and outflow of GCD) were noted in default mode network (DMN)-related areas and the cerebellum. GCD in the DMN midline core system, hippocampus, and cerebellum was closely correlated with the Mini- Mental State Examination and Functional Activities Questionnaire scores. In the ROC analysis combining VBM with GCD, the neuroimaging biomarker in the cerebellum was optimal for the early detection of MCI, whereas the precuneus was the best in predicting cognitive decline progression and AD diagnosis.

CONCLUSION

Changes in GM volume and directed functional connectivity may reflect the mechanism of cognitive decline. This discovery could improve our understanding of the pathology of AD and MCI and provide available neuroimaging markers for the early detection, progression, and diagnosis of AD and MCI.

CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation

Quantifying the volume of the cerebellum and its lobes is of profound interest in various neurodegenerative and acquired diseases. Especially for the most common spinocerebellar ataxias (SCA), for which the first antisense oligonculeotide-base gene silencing trial has recently started, there is an urgent need for quantitative, sensitive imaging markers at pre-symptomatic stages for stratification and treatment assessment. This work introduces CerebNet, a fully automated, extensively validated, deep learning method for the lobular segmentation of the cerebellum, including the separation of gray and white matter. For training, validation, and testing, T1-weighted images from 30 participants were manually annotated into cerebellar lobules and vermal sub-segments, as well as cerebellar white matter. CerebNet combines FastSurferCNN, a UNet-based 2.5D segmentation network, with extensive data augmentation, e.g. realistic non-linear deformations to increase the anatomical variety, eliminating additional preprocessing steps, such as spatial normalization or bias field correction. CerebNet demonstrates a high accuracy (on average 0.87 Dice and 1.742mm Robust Hausdorff Distance across all structures) outperforming state-of-the-art approaches. Furthermore, it shows high test-retest reliability (average ICC >0.97 on OASIS and Kirby) as well as high sensitivity to disease effects, including the pre-ataxic stage of spinocerebellar ataxia type 3 (SCA3). CerebNet is compatible with FreeSurfer and FastSurfer and can analyze a 3D volume within seconds on a consumer GPU in an end-to-end fashion, thus providing an efficient and validated solution for assessing cerebellum sub-structure volumes. We make CerebNet available as source-code (https://github.com/Deep-MI/FastSurfer).

Effects of apolipoprotein E4 genotype on cerebro-cerebellar connectivity, brain atrophy, and cognition in patients with Alzheimer's disease

INTRODUCTION

While several studies have substantially revealed the influence of the apolipoprotein E4 genotype (APOE4) on the vulnerability of Alzheimer's disease (AD), there are still far fewer studies investigating whether and how APOE4, in the absence of the amyloid-β (Aβ), alters regional brain atrophy, cerebro-cerebellar connectivity and cognitive performance in AD patients.

METHODS

We employed MRI and neuropsychological data from 234 old adults with AD dementia, including 143 APOE4-positive (with ε2/ε4, ε3/ε4, or ε4/ε4 alleles) and 91 APOE4-negative (with ε2/ε2, ε2/ε3 or ε3/ε3), to investigate the cerebro-cerebellar connectivity in three cerebro-cerebellar brain networks: default mode network, motor network and affective-limbic network. Amyloid PET images were used to evaluate individual Aβ burdens, later used as covariates. Regional volumetric and cortical thickness measures were quantified in both the cerebellum and the cerebrum using the cerebellum segmentation algorithm and Freesurfer5.3, respectively.

RESULTS

Our corrected functional connectivity (FC) results showed that APOE4 carriers (APOE4+) had lower FC within the cerebro-cerebellar motor network. In addition, significant group differences in regional cortical thickness were observed in the left Crus I, the right VIIB, left superior frontal, and right middle temporal gyri. Group differences in regional brain volumes were observed in the left lobule V and right parstriangularis. Furthermore, multiple linear regression analysis indicated that APOE4+ AD patients show greater episodic memory impairment.

CONCLUSION

Since amyloid-β, age, education, and gender were included as confounds in the statistical models, our findings suggest that APOE4 independently contributes to brain atrophy, disrupted FC, and associated memory declines in AD patients.

Reduction in manual asymmetry and decline in fine manual dexterity in right-handed older adults with mild cognitive impairment

Research in Parkinson's or Alzheimer's disease suggests that hand function is affected by neurodegenerative diseases. However, little is known about the relationship between hand function and mild cognitive impairment (MCI). Therefore, we conducted a kinematic analysis of unimanual hand movements in MCI patients to answer whether manual asymmetries and manual dexterity are affected or preserved in this condition. Forty-one MCI patients and fifty healthy controls were tested with the Purdue Pegboard test. All participants were right-handed. Kinematic analyses (by hand) were calculated for path length, angle, and linear and angular velocities during reaching, grasping, transport and inserting. Group differences were tested by with factorial MANOVAs and laterality indexes (LI) were assessed. Groups were compared on "Right-Left" hand correlations to identify kinematics that best single-out patients. Kinematics from grasping and inserting were significantly more deteriorated in the MCI group, while outcomes for reaching and transport denoted superior performance. LIs data showed symmetry of movements in the MCI group, during reaching and transport. Comparisons of "Right-Left" hand correlations revealed that kinematics in reaching and transport were more symmetrical in patients. This study showed a deterioration of fine manual dexterity, an enhancement in gross dexterity of upper-limbs, and symmetrical movements in MCI patients.

Quantitative Assessment of Resting-State Functional Connectivity MRI to Differentiate Amnestic Mild Cognitive Impairment, Late-Onset Alzheimer's Disease From Normal Subjects

BACKGROUND

Alzheimer disease (AD) is a neurological disorder with brain network dysfunction. Investigation of the brain network functional connectivity (FC) alterations using resting-state functional MRI (rs-fMRI) can provide valuable information about the brain network pattern in early AD diagnosis.

PURPOSE

To quantitatively assess FC patterns of resting-state brain networks and graph theory metrics (GTMs) to identify potential features for differentiation of amnestic mild cognitive impairment (aMCI) and late-onset AD from normal.

STUDY TYPE

Prospective.

SUBJECTS

A total of 14 normal, 16 aMCI, and 13 late-onset AD.

FIELD STRENGTH/SEQUENCE

A 3.0 T; rs-fMRI: single-shot 2D-EPI and T1-weighted structure: MPRAGE.

ASSESSMENT

By applying bivariate correlation coefficient and Fisher transformation on the time series of predefined ROIs' pairs, correlation coefficient matrixes and ROI-to-ROI connectivity (RRC) were extracted. By thresholding the RRC matrix (with a threshold of 0.15), a graph adjacency matrix was created to compute GTMs.

STATISTICAL TESTS

Region of interest (ROI)-based analysis: parametric multivariable statistical analysis (PMSA) with a false discovery rate using (FDR)-corrected P < 0.05 cluster-level threshold together with posthoc uncorrected P < 0.05 connection-level threshold. Graph-theory analysis (GTA): P-FDR-corrected < 0.05. One-way ANOVA and Chi-square tests were used to compare clinical characteristics.

RESULTS

PMSA differentiated AD from normal, with a significant decrease in FC of default mode, salience, dorsal attention, frontoparietal, language, visual, and cerebellar networks. Furthermore, significant increase in overall FC of visual and language networks was observed in aMCI compared to normal. GTA revealed a significant decrease in global-efficiency (28.05 < 45), local-efficiency (22.98 < 24.05), and betweenness-centrality (14.60 < 17.39) for AD against normal. Moreover, a significant increase in local-efficiency (33.46 > 24.05) and clustering-coefficient (25 > 20.18) were found in aMCI compared to normal.

DATA CONCLUSION

This study demonstrated resting-state FC potential as an indicator to differentiate AD, aMCI, and normal. GTA revealed brain integration and breakdown by providing concise and comprehensible statistics.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Cerebellum and Emotion in Social Behavior

Accumulating evidence suggests that the cerebellum plays a crucial role not only in the motor and cognitive domains but also in emotions and social behavior. In the present chapter, after a general introduction on the significance of the emotional components of social behavior, we describe recent efforts to understand the contributions of the cerebellum in social cognition focusing on the emotional and affective aspects. Specifically, starting from the description of the cerebello-cortical networks subtending the social-affective domains, we illustrate the most recent findings on the social cerebellum and the possible functional mechanisms by which the cerebellum modulate social-affective behavior. Finally, we discuss the possible consequences of cerebellar dysfunction in the social-affective domain, focusing on those neurological and psychopathological conditions in which emotional and social behavior difficulties have been described as being associated with cerebellar structural or functional alterations.

A Method for Bridging Population-Specific Genotypes to Detect Gene Modules Associated with Alzheimer's Disease

BACKGROUND

Genome-wide association studies have successfully identified variants associated with multiple conditions. However, generalizing discoveries across diverse populations remains challenging due to large variations in genetic composition. Methods that perform gene expression imputation have attempted to address the transferability of gene discoveries across populations, but with limited success.

METHODS

Here, we introduce a pipeline that combines gene expression imputation with gene module discovery, including a dense gene module search and a gene set variation analysis, to address the transferability issue. Our method feeds association probabilities of imputed gene expression with a selected phenotype into tissue-specific gene-module discovery over protein interaction networks to create higher-level gene modules.

RESULTS

We demonstrate our method's utility in three case-control studies of Alzheimer's disease (AD) for three different race/ethnic populations (Whites, African descent and Hispanics). We discovered 182 AD-associated genes from gene modules shared between these populations, highlighting new gene modules associated with AD.

CONCLUSIONS

Our innovative framework has the potential to identify robust discoveries across populations based on gene modules, as demonstrated in AD.

Automated brain volumetric program measuring regional brain atrophy in diagnosis of mild cognitive impairment and Alzheimer's disease dementia

A quantitative analysis of brain volume can assist in the diagnosis of Alzheimer's disease (AD) which is ususally accompanied by brain atrophy. With an automated analysis program Quick Brain Volumetry (QBraVo) developed for volumetric measurements, we measured regional volumes and ratios to evaluate their performance in discriminating AD dementia (ADD) and mild cognitive impairment (MCI) patients from normal controls (NC). Validation of QBraVo was based on intra-rater and inter-rater reliability with a manual measurement. The regional volumes and ratios to total intracranial volume (TIV) and to total brain volume (TBV) or total cerebrospinal fluid volume (TCV) were compared among subjects. The regional volume to total cerebellar volume ratio named Standardized Atrophy Volume Ratio (SAVR) was calculated to compare brain atrophy. Diagnostic performances to distinguish among NC, MCI, and ADD were compared between MMSE, SAVR, and the predictive model. In total, 56 NCs, 44 MCI, and 45 ADD patients were enrolled. The average run time of QBraVo was 5 min 36 seconds. Intra-rater reliability was 0.999. Inter-rater reliability was high for TBV, TCV, and TIV (R = 0.97, 0.89 and 0.93, respectively). The medial temporal SAVR showed the highest performance for discriminating ADD from NC (AUC = 0.808, diagnostic accuracy = 80.2%). The predictive model using both MMSE and medial temporal SAVR improved the diagnostic performance for MCI in NC (AUC = 0.844, diagnostic accuracy = 79%). Our results demonstrated QBraVo is a fast and accurate method to measure brain volume. The regional volume calculated as SAVR could help to diagnose ADD and MCI and increase diagnostic accuracy for MCI.

Cerebellar atrophy and its implications on gait in cerebral amyloid angiopathy

OBJECTIVE

Recent data suggest that cerebral amyloid angiopathy (CAA) causes haemorrhagic lesions in cerebellar cortex as well as subcortical cerebral atrophy. However, the potential effect of CAA on cerebellar tissue loss and its clinical implications have not been investigated.

METHODS

Our study included 70 non-demented patients with probable CAA, 70 age-matched healthy controls (HCs) and 70 age-matched patients with Alzheimer's disease (AD). The cerebellum was segmented into percent of cerebellar subcortical volume (pCbll-ScV) and percent of cerebellar cortical volume (pCbll-CV) represented as percent (p) of estimated total intracranial volume. We compared pCbll-ScV and pCbll-CV between patients with CAA, HCs and those with AD. Gait velocity (metres/second) was used to investigate gait function in patients with CAA.

RESULTS

Patients with CAA had significantly lower pCbll-ScV compared with both HC (1.49±0.1 vs 1.73±0.2, p<0.001) and AD (1.49±0.1 vs 1.66±0.24, p<0.001) and lower pCbll-CV compared with HCs (6.03±0.5 vs 6.23±0.6, p=0.028). Diagnosis of CAA was independently associated with lower pCbll-ScV compared with HCs (p<0.001) and patients with AD (p<0.001) in separate linear regression models adjusted for age, sex and presence of hypertension. Lower pCbll-ScV was independently associated with worse gait velocity (β=0.736, 95% CI 0.28 to 1.19, p=0.002) in a stepwise linear regression analysis including pCbll-CV along with other relevant variables.

INTERPRETATION

Patients with CAA show more subcortical cerebellar atrophy than HC or patients with AD and more cortical cerebellar atrophy than HCs. Reduced pCbll-ScV correlated with lower gait velocity in regression models including other relevant variables. Overall, this study suggests that CAA causes cerebellar injury, which might contribute to gait disturbance.

Cerebellum-Cortical Interaction in Spatial Navigation and Its Alteration in Dementias

The cerebellum has a homogeneous structure and performs different computational functions such as modulation/coordination of the communication between cerebral regions, and regulation/integration of sensory information. Albeit cerebellar activity is generally associated with motor functions, several recent studies link it to various cognitive functions, including spatial navigation. In addition, cerebellar activity plays a modulatory role in different cognitive domains and brain processes. Depending on the network involved, cerebellar damage results in specific functional alterations, even when no function loss might be detected. In the present review, we discuss evidence of brainstem degeneration and of a substantial reduction of neurons in nuclei connected to the inferior olivary nucleus in the early stages of Alzheimer’s disease. Based on the rich patterns of afferences from the inferior olive nucleus to the cerebellum, we argue that the subtle alterations in spatial navigation described in the early stages of dementia stem from alterations of the neuromodulatory functions of the cerebellum.

An Intelligent System for Early Recognition of Alzheimer's Disease Using Neuroimaging

Alzheimer's disease (AD) is a neurodegenerative disease that affects brain cells, and mild cognitive impairment (MCI) has been defined as the early phase that describes the onset of AD. Early detection of MCI can be used to save patient brain cells from further damage and direct additional medical treatment to prevent its progression. Lately, the use of deep learning for the early identification of AD has generated a lot of interest. However, one of the limitations of such algorithms is their inability to identify changes in the functional connectivity in the functional brain network of patients with MCI. In this paper, we attempt to elucidate this issue with randomized concatenated deep features obtained from two pre-trained models, which simultaneously learn deep features from brain functional networks from magnetic resonance imaging (MRI) images. We experimented with ResNet18 and DenseNet201 to perform the task of AD multiclass classification. A gradient class activation map was used to mark the discriminating region of the image for the proposed model prediction. Accuracy, precision, and recall were used to assess the performance of the proposed system. The experimental analysis showed that the proposed model was able to achieve 98.86% accuracy, 98.94% precision, and 98.89% recall in multiclass classification. The findings indicate that advanced deep learning with MRI images can be used to classify and predict neurodegenerative brain diseases such as AD.

Intrinsic Brain Activity Alterations in Patients With Mild Cognitive Impairment-to-Normal Reversion: A Resting-State Functional Magnetic Resonance Imaging Study From Voxel to Whole-Brain Level

Mild cognitive impairment (MCI) reversion refers to patients with MCI who revert from MCI to a normal cognitive state. Exploring the underlying neuromechanism of MCI reverters may contribute to providing new insights into the pathogenesis of Alzheimer's disease and developing therapeutic interventions. Information on patients with MCI and healthy controls (HCs) was collected from the Alzheimer's Disease Neuroimaging Initiative database. We redefined MCI reverters as patients with MCI whose logical memory scores changed from MCI to normal levels using the logical memory criteria. We explored intrinsic brain activity alterations in MCI reverters from voxel, regional, and whole-brain levels by comparing resting-state functional magnetic resonance imaging metrics of the amplitude of low-frequency of fluctuation (ALFF), the fractional amplitude of low-frequency fluctuation (fALFF), percent amplitude of fluctuation (PerAF), regional homogeneity (ReHo), and degree centrality (DC) between MCI reverters and HCs. Finally, partial correlation analyses were conducted between cognitive scale scores and resting-state functional magnetic resonance imaging metrics of brain regions, revealing significant group differences. Thirty-two patients with MCI from the Alzheimer's Disease Neuroimaging Initiative database were identified as reverters. Thirty-seven age-, sex-, and education-matched healthy individuals were also enrolled. At the voxel level, compared with the HCs, MCI reverters had increased ALFF, fALFF, and PerAF in the frontal gyrus (including the bilateral orbital inferior frontal gyrus and left middle frontal gyrus), increased PerAF in the left fusiform gyrus, and decreased ALFF and fALFF in the right inferior cerebellum. Regarding regional and whole-brain levels, MCI reverters showed increased ReHo in the left fusiform gyrus and right median cingulate and paracingulate gyri; increased DC in the left inferior temporal gyrus and left medial superior frontal; decreased DC in the right inferior cerebellum and bilateral insular gyrus relative to HCs. Furthermore, significant correlations were found between cognitive performance and neuroimaging changes. These findings suggest that MCI reverters show significant intrinsic brain activity changes compared with HCs, potentially related to the cognitive reversion of patients with MCI. These results enhance our understanding of the underlying neuromechanism of MCI reverters and may contribute to further exploration of Alzheimer's disease.

Reported Hearing Loss in Alzheimer's Disease Is Associated With Loss of Brainstem and Cerebellar Volume

Multiple epidemiological studies have revealed an association between presbycusis and Alzheimer’s Disease (AD). Unfortunately, the neurobiological underpinnings of this relationship are not clear. It is possible that the two disorders share a common, as yet unidentified, risk factor, or that hearing loss may independently accelerate AD pathology. Here, we examined the relationship between reported hearing loss and brain volumes in normal, mild cognitive impairment (MCI) and AD subjects using a publicly available database. We found that among subjects with AD, individuals that reported hearing loss had smaller brainstem and cerebellar volumes in both hemispheres than individuals without hearing loss. In addition, we found that these brain volumes diminish in size more rapidly among normal subjects with reported hearing loss and that there was a significant interaction between cognitive diagnosis and the relationship between reported hearing loss and these brain volumes. These data suggest that hearing loss is linked to brainstem and cerebellar pathology, but only in the context of the pathological state of AD. We hypothesize that the presence of AD-related pathology in both the brainstem and cerebellum creates vulnerabilities in these brain regions to auditory deafferentation-related atrophy. These data have implications for our understanding of the potential neural substrates for interactions between hearing loss and AD.

Cerebellar Dentate Connectivity across Adulthood: A Large-Scale Resting State Functional Connectivity Investigation

Cerebellar contributions to behavior in advanced age are of interest and importance, given its role in motor and cognitive performance. There are differences and declines in cerebellar structure in advanced age and cerebellar resting state connectivity is lower. However, the work on this area to date has focused on the cerebellar cortex. The deep cerebellar nuclei provide the primary cerebellar inputs and outputs to the cortex, as well as the spinal and vestibular systems. Dentate networks can be dissociated such that the dorsal region is associated with the motor cortex, whereas the ventral aspect is associated with the prefrontal cortex. However, whether dentato-thalamo-cortical networks differ across adulthood remains unknown. Here, using a large adult sample (n = 590) from the Cambridge Center for Ageing and Neuroscience, we investigated dentate connectivity across adulthood. We replicated past work showing dissociable resting state networks in the dorsal and ventral aspects of the dentate. In both seeds, we demonstrated that connectivity is lower with advanced age, indicating that connectivity differences extend beyond the cerebellar cortex. Finally, we demonstrated sex differences in dentate connectivity. This expands our understanding of cerebellar circuitry in advanced age and underscores the potential importance of this structure in age-related performance differences.

Novel insights into the relationship between cerebellum and dementia: A narrative review as a toolkit for clinicians

The role of the cerebellum in neurodegenerative disorders that target cognitive functions has been a subject of increasing interest over the past years. However, a review focused on making clinicians more aware of the role of the cerebellum in dementia is still missing. This narrative review explores the possible factors explaining the involvement of the cerebellum in different kinds of dementia by providing more insights on how this structure can be relevant in clinical practice. It emerged that, despite overlapping in specific areas, structural cerebellar alterations in dementia show a certain degree of disease-specificity. Furthermore, the relevance of cerebellar changes in dementia is corroborated by correlations observed between their topography and cognitive symptomatology, as well as by its previously ignored involvement of the cerebellum in early stages of dementia. Despite needing further investigations, these findings could become a useful diagnostic aid for clinicians that should not be overlooked, in particular for those individuals who do not show distinct and manifest brain or neuropsychological alterations, but that still make clinicians suspect the presence of a neurocognitive disease.

Cerebellar White Matter Disruption in Alzheimer's Disease Patients: A Diffusion Tensor Imaging Study

The cognitive role of the cerebellum has recently gained much attention, and its pivotal role in Alzheimer's disease (AD) has now been widely recognized. Diffusion tensor imaging (DTI) has been used to evaluate the disruption of the microstructural milieu in AD, and though several white matter (WM) tracts such as corpus callosum, inferior and superior longitudinal fasciculus, cingulum, fornix, and uncinate fasciculus have been evaluated in AD, data on cerebellar WM tracts are currently lacking. We performed a tractography-based DTI reconstruction of the middle cerebellar peduncle (MCP), and the left and right superior cerebellar peduncles separately (SCPL and SCPR) and addressed the differences in fractional anisotropy (FA), axial diffusivity (Dax), radial diffusivity (RD), and mean diffusivity (MD) in the three tracts between 50 patients with AD and 25 healthy subjects. We found that AD patients showed a lower FA and a higher RD compared to healthy subjects in MCP, SCPL, and SCPR. Moreover, higher MD was found in SCPR and SCPL and higher Dax in SCPL. This result is important as it challenges the traditional view that WM bundles in the cerebellum are unaffected in AD and might identify new targets for therapeutic interventions.

Differences Changes in Cerebellar Functional Connectivity Between Mild Cognitive Impairment and Alzheimer's Disease: A Seed-Based Approach

Background: Recent studies have discovered that functional connections are impaired among patients with Alzheimer's disease (AD), even at the preclinical stage. The cerebellum has been implicated as playing a role in cognitive processes. However, functional connectivity (FC) among cognitive sub-regions of the cerebellum in patients with AD and mild cognitive impairment (MCI) remains to be further elucidated. Objective: Our study aims to investigate the FC changes of the cerebellum among patients with AD and MCI, compared to healthy controls (HC). Additionally, we explored the role of cerebellum FC changes in the cognitive performance of all subjects. Materials: Resting-state functional magnetic resonance imaging (rs-fMRI) data from three different groups (28 AD patients, 26 MCI patients, and 30 HC) was collected. We defined cerebellar crus II and lobule IX as seed regions to assess the intragroup differences of cortico-cerebellar connectivity. Bias correlational analysis was performed to investigate the relationship between changes in FC and neuropsychological performance. Results: Compared to HC, AD patients had decreased FC within the caudate, limbic lobe, medial frontal gyrus (MFG), middle temporal gyrus, superior frontal gyrus, parietal lobe/precuneus, inferior temporal gyrus, and posterior cingulate gyrus. Interestingly, MCI patients demonstrated increased FC within inferior parietal lobe, and MFG, while they had decreased FC in the thalamus, inferior frontal gyrus, and superior frontal gyrus. Further analysis indicated that FC changes between the left crus II and the right thalamus, as well as between left lobule IX and the right parietal lobe, were both associated with cognitive decline in AD. Disrupted FC between left crus II and right thalamus, as well as between left lobule IX and right parietal lobe, was associated with attention deficit among subjects with MCI. Conclusion: These findings indicate that cortico-cerebellar FC in MCI and AD patients was significantly disrupted with different distributions, particularly in the default mode networks (DMN) and fronto-parietal networks (FPN) region. Increased activity within the fronto-parietal areas of MCI patients indicated a possible compensatory role for the cerebellum in cognitive impairment. Therefore, alterations in the cortico-cerebellar FC represent a novel approach for early diagnosis and a potential therapeutic target for early intervention.

Contributions of Cerebro-Cerebellar Default Mode Connectivity Patterns to Memory Performance in Mild Cognitive Impairment

BACKGROUND

The cerebral default mode network (DMN) can be mapped onto specific regions in the cerebellum, which are specifically vulnerable to atrophy in Alzheimer's disease (AD) patients.

OBJECTIVE

We set out to determine whether there are specific differences in the interaction between the cerebral and cerebellar DMN in amnestic mild cognitive impairment (aMCI) patients compared to healthy controls using resting-state functional MRI and whether these differences are relevant for memory performance.

METHODS

Eighteen patients with aMCI were age and education-matched to eighteen older adults and underwent 3T MR-imaging. We performed seed-based functional connectivity analysis between the cerebellar DMN seeds and the cerebral DMN.

RESULTS

Our results showed that compared to healthy older adults, aMCI patients showed lower anti-correlation between the cerebellar DMN and several cerebral DMN regions. Additionally, we showed that degradation of the anti-correlation between the cerebellar DMN and the medial frontal cortex is correlated with worse memory performance in aMCI patients.

CONCLUSION

These findings provide evidence that the cerebellar DMN and cerebral DMN are negatively correlated during rest in older individuals, and suggest that the reduced anti-correlated impacts the modulatory role of the cerebellum on cognitive functioning, in particular on the executive component of memory functions in neurodegenerative diseases.

Comparison of Cerebellar Grey Matter Alterations in Bipolar and Cerebellar Patients: Evidence from Voxel-Based Analysis

The aim of this study was to compare the patterns of cerebellar alterations associated with bipolar disease with those induced by the presence of cerebellar neurodegenerative pathologies to clarify the potential cerebellar contribution to bipolar affective disturbance. Twenty-nine patients affected by bipolar disorder, 32 subjects affected by cerebellar neurodegenerative pathologies, and 37 age-matched healthy subjects underwent a 3T MRI protocol. A voxel-based morphometry analysis was used to show similarities and differences in cerebellar grey matter (GM) loss between the groups. We found a pattern of GM cerebellar alterations in both bipolar and cerebellar groups that involved the anterior and posterior cerebellar regions (p = 0.05). The direct comparison between bipolar and cerebellar patients demonstrated a significant difference in GM loss in cerebellar neurodegenerative patients in the bilateral anterior and posterior motor cerebellar regions, such as lobules I-IV, V, VI, VIIIa, VIIIb, IX, VIIb and vermis VI, while a pattern of overlapping GM loss was evident in right lobule V, right crus I and bilateral crus II. Our findings showed, for the first time, common and different alteration patterns of specific cerebellar lobules in bipolar and neurodegenerative cerebellar patients, which allowed us to hypothesize a cerebellar role in the cognitive and mood dysregulation symptoms that characterize bipolar disorder.

Changes in Resting-State Functional Connectivity of Cerebellum in Amnestic Mild Cognitive Impairment and Alzheimer's Disease: A Case-Control Study

This case-control study is aimed to investigate the correlation of altered functional connectivity (FC) in cerebellum with cognitive impairment in amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD). The morphometric and resting-state FC MRI analysis including 46 participants with AD, 32 with aMCI and 42 age-matched normal controls (NCs) were conducted. We compared the cerebellar gray matter volume and cerebellar FC with cerebral cortical regions among three groups. To investigate the relationship of cerebellar FC with cognition, we measure the correlation of significant altered FC and individual cognitive domain. No significant morphometric differences of cerebellum was observed across three groups. The patients with AD had weaker cerebral cortical FCs in bilateral Crus I and left VIIb compared to NCs, and in bilateral Crus I compared to patients with aMCI. For patients with aMCI, the weaker FC were found between right Crus I, left VIIb and cerebral cortical regions compared to NCs. The strength of left cerebellar FC positively correlated with specific cognitive subdomains, including memory, executive function, visuospatial function, and global cognition in AD and aMCI. These findings demonstrated the alteration of cerebellar FC with cerebral cortical regions, and the correlation of cerebellar FC and cognitive impairment in AD and aMCI.

The cerebellum could serve as a potential imaging biomarker of dementia conversion in patients with amyloid-negative amnestic mild cognitive impairment

BACKGROUND AND PURPOSE

As part of network-specific neurodegeneration, changes in cerebellar gray matter (GM) volume and impaired cerebello-cerebral functional networks have been reported in Alzheimer disease (AD). Compared with healthy controls, a volume loss in the cerebellum has been observed in patients with continuum of AD. However, little is known about the anatomical or functional changes in patients with clinical AD but no brain amyloidosis. We aimed to identify the relationship between cerebellar volume and dementia conversion of amyloid-negative mild cognitive impairment (MCI).

METHODS

This study was a retrospective cohort study of patients over the age 50 years with amyloid-negative amnestic MCI who visited the memory clinic of Asan Medical Center with no less than a 36-month follow-up period. All subjects underwent detailed neuropsychological tests, 3 T brain magnetic resonance imaging scans including three-dimensional T1 imaging, and fluorine-18[F¹⁸ ]-florbetaben amyloid positron emission tomography scans. A spatially unbiased atlas template of the cerebellum and brainstem was used for analyzing cerebellar GM volume.

RESULTS

During the 36 months of follow-up, 39 of 107 (36.4%) patients converted to dementia from amnestic MCI. The converter group had more severe impairments in all visual memory tasks. In terms of volumetric analysis, reduced crus I/II volume adjusted with total intracranial volume, and age was observed in the converter group.

CONCLUSIONS

Significant cerebellar GM atrophy involving the bilateral crus I/II may be a novel imaging biomarker for predicting dementia progression in amyloid-negative amnestic MCI patients.

Elucidating the Risk Factors for Progression from Amyloid-Negative Amnestic Mild Cognitive Impairment to Dementia

BACKGROUND

Amyloid PET allows for the assessment of amyloid β status in the brain, distinguishing true Alzheimer's disease from Alzheimer's disease-mimicking conditions. Around 15-20% of patients with clinically probable Alzheimer's disease have been found to have no significant Alzheimer's pathology on amyloid PET. However, a limited number of studies had been conducted on this subpopulation in terms of clinical progression.

OBJECTIVE

We investigated the risk factors that could affect the progression to dementia in patients with amyloid-negative amnestic mild cognitive impairment (MCI).

METHODS

This study was a single-institutional, retrospective cohort study of patients over the age of 50 with amyloid-negative amnestic MCI who visited the memory clinic of Asan Medical Center with a follow-up period of more than 36 months. All participants underwent brain magnetic resonance imaging (MRI), detailed neuropsychological testing, and fluorine-18[F18]-florbetaben amyloid PET.

RESULTS

During the follow-up period, 39 of 107 patients progressed to dementia from amnestic MCI. In comparison with the stationary group, the progressed group had a more severe impairment in verbal and visual episodic memory function and hippocampal atrophy, which showed an Alzheimer's diseaselike pattern despite the lack of evidence for significant Alzheimer's disease pathology. Voxel-based morphometric MRI analysis revealed that the progressed group had a reduced gray matter volume in the bilateral cerebellar cortices, right temporal cortex, and bilateral insular cortices.

CONCLUSION

Considering the lack of evidence of amyloid pathology, clinical progression of these subpopulation may be caused by other neuropathologies such as TDP-43, abnormal tau or alpha synuclein that lead to neurodegeneration independent of amyloid-driven pathway. Further prospective studies incorporating biomarkers of Alzheimer's disease-mimicking dementia are warranted.

Cerebellar Volume Is Associated with Cognitive Decline in Mild Cognitive Impairment: Results from ADNI

Alzheimer's disease (AD) is a disease with dysfunctional brain network. Previous studies found the cerebellar volume changes over the course of AD disease progression; however, whether cerebellar volume change contributes to the cognitive decline in AD, or its earlier disease stage (i.e., mild cognitive impairment [MCI]) remains unclear. In ADNI, cognitive function was assessed using Alzheimer's Disease Assessment Scale-Cognitive Behavior section (ADAS-Cog). We used linear regression and linear mixed effects models to examine whether cerebellar volume is associated with either baseline cognition or with cognitive changes over time in MCI or in AD. We used logistic regression to assess the relationship between cerebellar volume and disease progression to MCI and AD. We found that cerebellar volume is associated with cognition in patients with MCI, after adjusting for age, gender, education, hippocampal volume, and APOE4 status. Consistently, cerebellar volume is associated with increased odds of the disease stages of MCI and AD when compared to controls. However, cerebellar volume is not associated with cognitive changes over time in either MCI or AD. In summary, cerebellar volume may contribute to cognition level in MCI, but not in AD, indicating that the cerebellar network might modulate the cognitive function in the early stage of the disease. The cerebellum may be a potential target for neuromodulation in treating MCI.

Assessment of plaque morphology in Alzheimer's mouse cerebellum using three-dimensional X-ray phase-based virtual histology

Visualization and characterization of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta$$\end{document}β-amyloid deposits is a fundamental task in pre-clinical study of Alzheimer’s disease (AD) to assess its evolution and monitor the efficiency of new therapeutic strategies. While the cerebellum is one of the brain areas most underestimated in the context of AD, renewed interest in cerebellar lesions has recently arisen as they may link to motor and cognitive alterations. Thus, we quantitatively investigated three-dimensional plaque morphology in the cerebellum in APP/PS1 transgenic mouse, as a model of AD. In order to obtain a complete high-resolution three-dimensional view of the investigated tissue, we exploited synchrotron X-ray phase contrast tomography (XPCT), providing virtual slices with histology-matching resolution. We found the formation of plaques elongated in shape, and with a specific orientation in space depending on the investigated region of the cerebellar cortex. Remarkably, a similar shape is observed in human cerebellum from demented patients. Our findings demonstrate the capability of XPCT in volumetric quantification, supporting the current knowledge about plaque morphology in the cerebellum and the fundamental role of the surrounding tissue in driving their evolution. A good correlation with the human neuropathology is also reported.

Effects of Cerebellar Theta Burst Stimulation on Contralateral Motor Cortex Excitability in Patients with Alzheimer's Disease

Although the cerebellum is not among the most renowned brain structures affected in Alzheimer`s disease (AD), recent evidence suggest that it undergoes degenerative changes during the course of the disease. A main neurophysiological feature of AD patients is the remarkable impairment of long term potentiation (LTP)-like cortical plasticity assessed in the primary motor cortex (M1) using theta burst stimulation (TBS) protocols. In healthy conditions, continuous (cTBS) and intermittent TBS (iTBS) of the cerebellum induce respectively long term depression (LTD)-like and LTP-like after effects in the contralateral M1. Here we aimed at examining the effects of cerebellar TBS on contralateral M1 excitability in a sample of 15 AD patients and 12 healthy age matched controls (HS). Motor evoked potentials (MEPs) were obtained in the contralateral M1 before and after cerebellar cTBS and iTBS protocols. As compared to HS, AD patients showed an impairment of LTP-like cortical plasticity mechanisms following cerebellar iTBS. No difference was observed for the cTBS protocol, in which both populations exhibited the expected LTD-like after effect. This study shows that mechanisms of cerebellar-cortical plasticity are impaired in AD. Given its role in high order cognitive functions, new potential therapeutic strategies could be built up in the future to modulate neural activity in the cerebellum in AD.

A Novel Connectome-Based Electrophysiological Study of Subjective Cognitive Decline Related to Alzheimer's Disease by Using Resting-State High-Density EEG EGI GES 300

Aim: To investigate for the first time the brain network in the Alzheimer’s disease (AD) spectrum by implementing a high-density electroencephalography (HD-EEG - EGI GES 300) study with 256 channels in order to seek if the brain connectome can be effectively used to distinguish cognitive impairment in preclinical stages. Methods: Twenty participants with AD, 30 with mild cognitive impairment (MCI), 20 with subjective cognitive decline (SCD) and 22 healthy controls (HC) were examined with a detailed neuropsychological battery and 10 min resting state HD-EEG. We extracted correlation matrices by using Pearson correlation coefficients for each subject and constructed weighted undirected networks for calculating clustering coefficient (CC), strength (S) and betweenness centrality (BC) at global (256 electrodes) and local levels (29 parietal electrodes). Results: One-way ANOVA presented a statistically significant difference among the four groups at local level in CC [F (3, 88) = 4.76, p = 0.004] and S [F (3, 88) = 4.69, p = 0.004]. However, no statistically significant difference was found at a global level. According to the independent sample t-test, local CC was higher for HC [M (SD) = 0.79 (0.07)] compared with SCD [M (SD) = 0.72 (0.09)]; t (40) = 2.39, p = 0.02, MCI [M (SD) = 0.71 (0.09)]; t (50) = 0.41, p = 0.004 and AD [M (SD) = 0.68 (0.11)]; t (40) = 3.62, p = 0.001 as well, while BC showed an increase at a local level but a decrease at a global level as the disease progresses. These findings provide evidence that disruptions in brain networks in parietal organization may potentially represent a key factor in the ability to distinguish people at early stages of the AD continuum. Conclusions: The above findings reveal a dynamically disrupted network organization of preclinical stages, showing that SCD exhibits network disorganization with intermediate values between MCI and HC. Additionally, these pieces of evidence provide information on the usefulness of the 256 HD-EEG in network construction.

Behavioral psychological symptoms of dementia and functional connectivity changes: a network-based study

Behavioral and psychological symptoms of dementia (BPSD) are commonly observed since the early stage of Alzheimer's disease (AD) associated with structural brain changes. It is conceivable that they may also relate to functional brain changes. This resting-state functional MRI (RS-fMRI) study investigated the alterations within functional brain networks of a cohort of AD patients at different clinical stages who presented with BPSD. One hundred one AD patients and 56 patients with amnestic mild cognitive impairment underwent a neuropsychological evaluation including the Neuropsychiatry Inventory-12 (NPI-12). All patients and 35 healthy controls (HS) underwent 3T-MRI. Factor analysis was used to extract the principal factors from NPI-12, while RS-fMRI data were processed using graph theory to investigate functional connectivity. Five factors were extracted from NPI-12. Sixty-two percent of patients showed BPSD and functional brain connectivity changes in various networks compared to those without BPSD and HS. These changes contributed to account for patients' BPSD. This work opens new perspectives in terms of nonpharmacological interventions that might be designed to modulate brain connectivity and improve patients' BPSD.

Radiological classification of dementia from anatomical MRI assisted by machine learning-derived maps

BACKGROUND AND PURPOSE

Many artificial intelligence tools are currently being developed to assist diagnosis of dementia from magnetic resonance imaging (MRI). However, these tools have so far been difficult to integrate in the clinical routine workflow. In this work, we propose a new simple way to use them and assess their utility for improving diagnostic accuracy.

MATERIALS AND METHODS

We studied 34 patients with early-onset Alzheimer's disease (EOAD), 49 with late-onset AD (LOAD), 39 with frontotemporal dementia (FTD) and 24 with depression from the pre-existing cohort CLIN-AD. Support vector machine (SVM) automatic classifiers using 3D T1 MRI were trained to distinguish: LOAD vs. Depression, FTD vs. LOAD, EOAD vs. Depression, EOAD vs. FTD. We extracted SVM weight maps, which are tridimensional representations of discriminant atrophy patterns used by the classifier to take its decisions and we printed posters of these maps. Four radiologists (2 senior neuroradiologists and 2 unspecialized junior radiologists) performed a visual classification of the 4 diagnostic pairs using 3D T1 MRI. Classifications were performed twice: first with standard radiological reading and then using SVM weight maps as a guide.

RESULTS

Diagnostic performance was significantly improved by the use of the weight maps for the two junior radiologists in the case of FTD vs. EOAD. Improvement was over 10 points of diagnostic accuracy.

CONCLUSION

This tool can improve the diagnostic accuracy of junior radiologists and could be integrated in the clinical routine workflow.

Disrupted functional connectivity of the locus coeruleus in healthy adults with parental history of Alzheimer's disease

Prevention and early treatment strategies for Alzheimer's disease (AD) are hampered by the lack of research biomarkers. Neuropathological changes in the Locus Coeruleus (LC) are detected early in AD, and noradrenaline plays a neuroprotective role in LC projecting areas. We assessed functional connectivity (FC) of the brainstem in asymptomatic individuals at familial risk for AD hypothesizing that FC of the LC will be decreased in relation to not-at-risk individuals. Thirty-one offspring of patients with late-onset AD (O-LOAD) (22 females; mean age ± SD = 50.36 ± 8.32) and 28 healthy controls (HC) (20 females; mean age ± SD = 53.90 ± 8.44) underwent a neurocognitive evaluation and a resting-state functional magnetic resonance imaging acquisition. In FC analyses we evaluated whole-brain global connectivity of the brainstem area, and subsequently assessed seed-to-voxel FC patterns from regions showing between-group differences. O-LOAD individuals scored worse in neurocognitive measures of memory and overall functioning (p_FDR<0.05). In imaging analyses, we observed that O-LOAD individuals showed decreased global connectivity in a cluster encompassing the left LC (peak = -4, -34, -32, p_TFCE<0.05). Seed-to-voxel analyses revealed that this finding was largely explained by decreased connectivity between the LC and the cerebellar cortex. Moreover, FC between the LC and the left cerebellum correlated positively with delayed recall scores. FC between the LC and the cerebellar cortex is decreased in the healthy offspring of patients with LOAD, such connectivity measurements being associated with delayed memory scores. The assessment of FC between the LC and the cerebellum may serve as a biomarker of AD vulnerability.

Unsuspected Involvement of Spinal Cord in Alzheimer Disease

Objective: Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer's disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia. Methods: 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features (ρ > 0.7) were removed, and the best subset identified for patients' classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors. Results: Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. Discussion: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD.

Cerebellar dentate nucleus functional connectivity with cerebral cortex in Alzheimer's disease and memory: a seed-based approach

Alzheimer's disease (AD) is a chronic neurodegenerative disorder characterized by specific patterns of gray and white matter damage and cognitive/behavioral manifestations. The cerebellum has also been implicated in the pathophysiology of AD. Because the cerebellum is known to have strong functional connectivity (FC) with associative cerebral cortex regions, it is possible to hypothesize that it is incorporated into intrinsic FC networks relevant to cognitive manifestation of AD. In the present study, the cerebellar dentate nucleus, the largest cerebellar nucleus and the major output channel to the cerebral cortex, was chosen as the region of interest to test potential cerebellocerebral FC alterations and correlations with patients' memory impairment in a group of patients with AD. Compared to controls, patients with AD showed an increase in FC between the dentate nucleus and regions of the lateral temporal lobe. This study demonstrates that lower memory performances in AD may be related to altered FC within specific cerebellocortical functional modules, thus suggesting the cerebellar contribution to AD pathophysiology and typical memory dysfunctions.

A promising structural magnetic resonance imaging assessment in patients with preclinical cognitive decline and diabetes mellitus

Subjective cognitive decline (SCD) is frequently reported in diabetic patients. Diabetes mellitus (DM) is associated with changes in the microstructure of the brain arise in diabetic patients, including changes in gray matter volume (GMV). However, the underlying mechanisms of changes in GMV in DM patients with cognitive impairment remain uncertain. Here, we present an overview of amyloid-β-dependent cognitive impairment in DM patients with SCD. Moreover, we review the evolving insights from studies on the GMV changes in GMV and cognitive dysfunction to which provide the mechanisms of cognitive impairment in T2DM. Ultimately, the novel structural magnetic resonance imaging (MRI) protocol was used for detecting neuroimaging biomarkers that can predict the clinical outcomes in diabetic patients with SCD. A reliable MRI protocol would be helpful to detect neurobiomarkers, and to understand the pathological mechanisms of preclinical cognitive impairment in diabetic patients.