Sequential relationships between grey matter and white matter atrophy and brain metabolic abnormalities in early Alzheimer's disease

Frontal-striatal glucose metabolism and fatigue in patients with multiple sclerosis, long COVID, and COVID-19 recovered controls

This study compared brain glucose metabolism using FDG-PET in the caudate nucleus, putamen, globus pallidus, thalamus, and dorsolateral prefrontal cortex (DLPFC) among patients with Long COVID, patients with fatigue, people with multiple sclerosis (PwMS) patients with fatigue, and COVID recovered controls. PwMS exhibited greater hypometabolism compared to long COVID patients with fatigue and the COVID recovered control group in all studied brain areas except the globus pallidus (effect size range 0.7-1.5). The results showed no significant differences in glucose metabolism between patients with Long COVID and the COVID recovered control group in these regions. These findings suggest that long COVID fatigue may involve non-CNS systems, neurotransmitter imbalances, or psychological factors not captured by FDG-PET, while MS-related fatigue is associated with more severe frontal-striatal circuit dysfunction due to demyelination and neurodegeneration. Symmetrical standardized uptake values (SUVs) between hemispheres in all groups imply that fatigue in these conditions may be related to global or network-level alterations rather than hemisphere-specific changes. Future studies should employ fine-grained analysis methods, explore other brain regions, and control for confounding factors to better understand the pathophysiology of fatigue in MS and long COVID. Longitudinal studies tracking brain glucose metabolism in patients with Long COVID could provide insights into the evolution of metabolic patterns as the condition progresses.

Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer's disease from cognitively unimpaired amyloid-positive individuals

Differentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer's disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.

Spatial and Temporal Relationships Between Atrophy and Hypometabolism in Behavioral-Variant Frontotemporal Dementia

PURPOSE

Individuals with behavioral-variant frontotemporal dementia (bvFTD) show changes in brain structure as assessed by MRI and brain function assessed by 18FDG-PET hypometabolism. However, current understanding of the spatial and temporal interplay between these measures remains limited.

METHODS

Here, we examined longitudinal atrophy and hypometabolism relationships in 15 bvFTD subjects with 2 to 4 follow-up MRI and PET scans (56 visits total). Subject-specific slopes of atrophy and hypometabolism over time were extracted across brain regions and correlated with baseline measures both locally, via Pearson correlations, and nonlocally, via sparse canonical correlation analyses (SCCA).

RESULTS

Notably, we identified a robust link between initial hypometabolism and subsequent cortical atrophy rate changes in bvFTD subjects. Network-level exploration unveiled alignment between baseline hypometabolism and ensuing atrophy rates in the dorsal attention, language, and default mode networks. SCCA identified 2 significant and highly localized components depicting the connection between baseline hypometabolism and atrophy slope over time. The first centered around bilateral orbitofrontal, frontopolar, and medial prefrontal lobes, whereas the second concentrated in the left temporal lobe and precuneus.

CONCLUSIONS

This study highlights 18FDG-PET as a dependable predictor of forthcoming atrophy in spatially adjacent brain regions for individuals with bvFTD.

Functional and structural abnormalities of the speech disorders: a multimodal activation likelihood estimation meta-analysis

Speech disorders are associated with different degrees of functional and structural abnormalities. However, the abnormalities associated with specific disorders, and the common abnormalities shown by all disorders, remain unclear. Herein, a meta-analysis was conducted to integrate the results of 70 studies that compared 1843 speech disorder patients (dysarthria, dysphonia, stuttering, and aphasia) to 1950 healthy controls in terms of brain activity, functional connectivity, gray matter, and white matter fractional anisotropy. The analysis revealed that compared to controls, the dysarthria group showed higher activity in the left superior temporal gyrus and lower activity in the left postcentral gyrus. The dysphonia group had higher activity in the right precentral and postcentral gyrus. The stuttering group had higher activity in the right inferior frontal gyrus and lower activity in the left inferior frontal gyrus. The aphasia group showed lower activity in the bilateral anterior cingulate gyrus and left superior frontal gyrus. Across the four disorders, there were concurrent lower activity, gray matter, and fractional anisotropy in motor and auditory cortices, and stronger connectivity between the default mode network and frontoparietal network. These findings enhance our understanding of the neural basis of speech disorders, potentially aiding clinical diagnosis and intervention.

Classification Prediction of Alzheimer's Disease and Vascular Dementia Using Physiological Data and ECD SPECT Images

Alzheimer's disease (AD) and vascular dementia (VaD) are the two most common forms of dementia. However, their neuropsychological and pathological features often overlap, making it difficult to distinguish between AD and VaD. In addition to clinical consultation and laboratory examinations, clinical dementia diagnosis in Taiwan will also include Tc-99m-ECD SPECT imaging examination. Through machine learning and deep learning technology, we explored the feasibility of using the above clinical practice data to distinguish AD and VaD. We used the physiological data (33 features) and Tc-99m-ECD SPECT images of 112 AD patients and 85 VaD patients in the Taiwanese Nuclear Medicine Brain Image Database to train the classification model. The results, after filtering by the number of SVM RFE 5-fold features, show that the average accuracy of physiological data in distinguishing AD/VaD is 81.22% and the AUC is 0.836; the average accuracy of training images using the Inception V3 model is 85% and the AUC is 0.95. Finally, Grad-CAM heatmap was used to visualize the areas of concern of the model and compared with the SPM analysis method to further understand the differences. This research method can quickly use machine learning and deep learning models to automatically extract image features based on a small amount of general clinical data to objectively distinguish AD and VaD.

The Role of the Anterior Thalamic Nuclei in the Genesis of Memory Disorders in Alzheimer's Disease: An Exploratory Study

BACKGROUND

Increasing evidence is demonstrating that degeneration of specific thalamic nuclei, in addition to the hippocampus, may occur in Alzheimer's disease (AD) from the prodromal stage (mild cognitive impairment - MCI) and contribute to memory impairment.

OBJECTIVE

Here, we evaluated the presence of macro and micro structural alterations at the level of the anterior thalamic nuclei (ATN) and medio-dorsal thalamic nuclei (MDTN) in AD and amnestic MCI (aMCI) and the possible relationship between such changes and the severity of memory impairment.

METHODS

For this purpose, a sample of 50 patients with aMCI, 50 with AD, and 50 age- and education-matched healthy controls (HC) were submitted to a 3-T MRI protocol with whole-brain T1-weighted and diffusion tensor imaging and a comprehensive neuropsychological assessment.

RESULTS

At macro-structural level, both the ATN and MDTN were found significantly smaller in patients with aMCI and AD when compared to HC subjects. At micro-structural level, instead, diffusion alterations that significantly differentiated aMCI and AD patients from HC subjects were found only in the ATN, but not in the MDTN. Moreover, diffusion values of the ATN were significantly associated with poor episodic memory in the overall patients' group.

CONCLUSIONS

These findings represent the first in vivo evidence of a relevant involvement of ATN in the AD-related neurodegeneration and memory profile and strengthen the importance to look beyond the hippocampus when considering neurological conditions characterized by memory decline.

Calculation of cerebral hemispheres volume values (grey matter, white matter and lateral ventricle) of sheep and goat: A stereological study

Stereology is a discipline that allows us to obtain quantitative information about the geometric structure of three-dimensional objects. In this study, the volume of grey matter (GM), white matter (WM), and lateral ventricle (LV) of the cerebral hemispheres (CH) in sheep and goats were calculated. For this purpose, six healthy male sheep and goat brains (1-2 years old) without any anomaly were used. Brains were fixed with 10% formaldehyde in the skull. The skull was opened using standard anatomical dissection methods, and the brains were carefully removed. Brain weight and volume were measured (using Archimedes' principle) after the meninges were removed. The cerebral hemispheres were separated from the other parts of the brain by a section made in front of the rostral colliculus. In the same way, the weight and volume of the cerebral hemispheres were measured. Afterward, the cerebral hemispheres were blocked with agar, and transversal cross sections (from rostral to caudal) with an average thickness of 3.42 mm were taken from the cerebral hemispheres. Grey matter was stained with Berlin blue macroscopic staining method. The stained cross sections were scanned at 600 dpi resolution, and a point counting grid was placed on the images with the ImageJ software. Cavalieri's principle calculated the surface area and volume measurements of the grey matter, white matter, and lateral ventricle. GM, WM, and LV volumes in sheep and goat cerebral hemispheres were calculated as 54.94, 21.48 and 3.06 mL in sheep, 57.46, 24.13 and 3.12 mL in goats, respectively. The percentages of these structures in the total hemisphere volume were 71.83%, 28.17% and 4.00% in sheep, 70.42%, 29.58% and 3.82% in goats, respectively. Asymmetry was not observed in cerebral hemispheres in both species. A difference was found in the WM, LV and LV: CH ratios in the right/left comparison of the goat (p < 0.05). In comparing sheep and goats, a significant difference was observed in WM right, WM left, WM total, CH left and CH total (p < 0.05). In conclusion, the cerebral hemispheres' grey matter and white matter ratio are frequently used to diagnose neurodegenerative diseases. In recent years, the increase in neurodegenerative disease models in farm animals has been enormous. It is thought that these values obtained from healthy animals in the current study will be important for such experimental studies in the future.

Disentangling in-vivo microstructural changes of white and gray matter in mild cognitive impairment and Alzheimer's disease: a systematic review and meta-analysis

The microstructural characteristics of white and gray matter in mild cognitive impairment (MCI) and the early-stage of Alzheimer's disease (AD) remain unclear. This study aimed to systematically identify the microstructural damages of MCI/AD in studies using neurite orientation dispersion and density imaging (NODDI), and explore their correlations with cognitive performance. Multiple databases were searched for eligible studies. The 10 eligible NODDI studies were finally included. Patients with MCI/AD showed overall significant reductions in neurite density index (NDI) of specific white matter structures in bilateral hemispheres (left hemisphere: -0.40 [-0.53, -0.27], P < 0.001; right: -0.33 [-0.47, -0.19], P < 0.001), involving the bilateral superior longitudinal fasciculus (SLF), uncinate fasciculus (UF), the left posterior thalamic radiation (PTR), and the left cingulum. White matter regions exhibited significant increased orientation dispersion index (ODI) (left: 0.25 [0.02, 0.48], P < 0.05; right: 0.27 [0.07, 0.46], P < 0.05), including the left cingulum, the right UF, and the bilateral parahippocampal cingulum (PHC), and PTR. Additionally, the ODI of gray matter showed significant reduction in bilateral hippocampi (left: -0.97 [-1.42, -0.51], P < 0.001; right: -0.90 [-1.35, -0.45], P < 0.001). The cognitive performance in MCI/AD was significantly associated with NDI (r = 0.50, P < 0.001). Our findings highlight the microstructural changes in MCI/AD were characterized by decreased fiber orientation dispersion in the hippocampus, and decreased neurite density and increased fiber orientation dispersion in specific white matter tracts, including the cingulum, UF, and PTR. Moreover, the decreased NDI may indicate the declined cognitive level of MCI/AD patients.

Hippocampal metabolic subregions and networks: Behavioral, molecular, and pathological aging profiles

INTRODUCTION

Hippocampal local and network dysfunction is the hallmark of Alzheimer's disease (AD).

METHODS

We characterized the spatial patterns of hippocampus differentiation based on brain co-metabolism in healthy elderly participants and demonstrated their relevance to study local metabolic changes and associated dysfunction in pathological aging.

RESULTS

The hippocampus can be differentiated into anterior/posterior and dorsal cornu ammonis (CA)/ventral (subiculum) subregions. While anterior/posterior CA show co-metabolism with different regions of the subcortical limbic networks, the anterior/posterior subiculum are parts of cortical networks supporting object-centered memory and higher cognitive demands, respectively. Both networks show relationships with the spatial patterns of gene expression pertaining to cell energy metabolism and AD's process. Finally, while local metabolism is generally lower in posterior regions, the anterior-posterior imbalance is maximal in late mild cognitive impairment with the anterior subiculum being relatively preserved.

DISCUSSION

Future studies should consider bidimensional hippocampal differentiation and in particular the posterior subicular region to better understand pathological aging.

The association between post-traumatic stress disorder (PTSD) and cognitive impairment: A systematic review of neuroimaging findings

BACKGROUND

Accumulating evidence suggests that post-traumatic stress disorder (PTSD) may increase the risk of various types of dementia. Despite the large number of studies linking these critical conditions, the underlying mechanisms remain unclear. The past decade has witnessed an exponential increase in interest on brain imaging research to assess the neuroanatomical underpinnings of PTSD. This systematic review provides a critical assessment of available evidence of neuroimaging correlates linking PTSD to a higher risk of dementia.

METHODS

The EMBASE, PubMed/MEDLINE, and SCOPUS electronic databases were systematically searched from 1980 to May 22, 2021 for original references on neuroimaging correlates of PTSD and risk of dementia. Literature search, screening of references, methodological quality appraisal of included articles as well as data extractions were independently conducted by at least two investigators. Eligibility criteria included: 1) a clear PTSD definition; 2) a subset of included participants must have developed dementia or cognitive impairment at any time point after the diagnosis of PTSD through any diagnostic criteria; and 3) brain imaging protocols [structural, molecular or functional], including whole-brain morphologic and functional MRI, and PET imaging studies linking PTSD to a higher risk of cognitive impairment/dementia.

RESULTS

Overall, seven articles met eligibility criteria, comprising findings from 366 participants with PTSD. Spatially convergent structural abnormalities in individuals with PTSD and co-occurring cognitive dysfunction involved primarily the bilateral frontal (e.g., prefrontal, orbitofrontal, cingulate cortices), temporal (particularly in those with damage to the hippocampi), and parietal (e.g., superior and precuneus) regions.

LIMITATIONS

A meta-analysis could not be performed due to heterogeneity and paucity of measurable data in the eligible studies.

CONCLUSIONS

Our systematic review provides putative neuroimaging correlates associated with PTSD and co-occurring dementia/cognitive impairment particularly involving the hippocampi. Further research examining neuroimaging features linking PTSD to dementia are clearly an unmet need of the field. Future imaging studies should provide a better control for relevant confounders, such as the selection of more homogeneous samples (e.g., age, race, education), a proper control for co-occurring disorders (e.g., co-occurring major depressive and anxiety disorders) as well as the putative effects of psychotropic medication use. Furthermore, prospective studies examining imaging biomarkers associated with a higher rate of conversion from PTSD to dementia could aid in the stratification of people with PTSD at higher risk for developing dementia for whom putative preventative interventions could be especially beneficial.

EEG resting-state networks in Alzheimer's disease associated with clinical symptoms

Alzheimer's disease (AD) is a progressive neuropsychiatric disease affecting many elderly people and is characterized by progressive cognitive impairment of memory, visuospatial, and executive functions. As the elderly population is growing, the number of AD patients is increasing considerably. There is currently growing interest in determining AD's cognitive dysfunction markers. We used exact low-resolution-brain-electromagnetic-tomography independent-component-analysis (eLORETA-ICA) to assess activities of five electroencephalography resting-state-networks (EEG-RSNs) in 90 drug-free AD patients and 11 drug-free patients with mild-cognitive-impairment due to AD (ADMCI). Compared to 147 healthy subjects, the AD/ADMCI patients showed significantly decreased activities in the memory network and occipital alpha activity, where the age difference between the AD/ADMCI and healthy groups was corrected by linear regression analysis. Furthermore, the age-corrected EEG-RSN activities showed correlations with cognitive function test scores in AD/ADMCI. In particular, decreased memory network activity showed correlations with worse total cognitive scores for both Mini-Mental-State-Examination (MMSE) and Alzheimer's Disease-Assessment-Scale-cognitive-component-Japanese version (ADAS-J cog) including worse sub-scores for orientation, registration, repetition, word recognition and ideational praxis. Our results indicate that AD affects specific EEG-RSNs and deteriorated network activity causes symptoms. Overall, eLORETA-ICA is a useful, non-invasive tool for assessing EEG-functional-network activities and provides better understanding of the neurophysiological mechanisms underlying the disease.

Synaptic loss and gliosis in the nucleus tractus solitarii with streptozotocin-induced Alzheimer's disease

Obstructive sleep apnea is highly prevalent in Alzheimer's disease (AD). However, brainstem centers controlling respiration have received little attention in AD research, and mechanisms behind respiratory dysfunction in AD are not understood. The nucleus tractus solitarii (nTS) is an important brainstem center for respiratory control and chemoreflex function. Alterations of nTS integrity, like those shown in AD patients, likely affect neuronal processing and adequate control of breathing. We used the streptozotocin-induced rat model of AD (STZ-AD) to analyze cellular changes in the nTS that corroborate previously documented respiratory dysfunction. We used 2 common dosages of STZ (2 and 3 mg/kg STZ) for model induction and evaluated the early impact on cell populations in the nTS. The hippocampus served as control region to identify site-specific effects of STZ. There was significant atrophy in the caudal nTS of the 3 mg/kg STZ-AD group only, an area known to integrate chemoafferent information. Also, the hippocampus had significant atrophy with the highest STZ dosage tested. Both STZ-AD groups showed respiratory dysfunction along with multiple indices for astroglial and microglial activation. These changes were primarily located in the caudal and intermediate nTS. While there was no change of astrocytes in the hippocampus, microglial activation was accompanied by a reduction in synaptic density. Together, our data demonstrate that STZ-AD induces site-specific effects on all major cell types, primarily in the caudal/intermediate nTS. Both STZ dosages used in this study produced a similar outcome and can be used for future studies examining the initial symptoms of STZ-AD.

How Can Insulin Resistance Cause Alzheimer's Disease?

Alzheimer's disease (AD) is a neurodegenerative disorder associated with cognitive decline. Despite worldwide efforts to find a cure, no proper treatment has been developed yet, and the only effective countermeasure is to prevent the disease progression by early diagnosis. The reason why new drug candidates fail to show therapeutic effects in clinical studies may be due to misunderstanding the cause of AD. Regarding the cause of AD, the most widely known is the amyloid cascade hypothesis, in which the deposition of amyloid beta and hyperphosphorylated tau is the cause. However, many new hypotheses were suggested. Among them, based on preclinical and clinical evidence supporting a connection between AD and diabetes, insulin resistance has been pointed out as an important factor in the development of AD. Therefore, by reviewing the pathophysiological background of brain metabolic insufficiency and insulin insufficiency leading to AD pathology, we will discuss how can insulin resistance cause AD.

Longitudinal Spatial Relationships Between Atrophy and Hypometabolism Across the Alzheimer's Disease Continuum

BACKGROUND

The A/T/N framework allows for the assessment of pathology-specific markers of MRI-derived structural atrophy and hypometabolism on 18FDG-PET. However, how these measures relate to each other locally and distantly across pathology-defined A/T/N groups is currently unclear.

OBJECTIVE

To determine the regions of association between atrophy and hypometabolism in A/T/N groups both within and across time points.

METHODS

We examined multivariate multimodal neuroimaging relationships between MRI and 18FDG-PET among suspected non-Alzheimer's disease pathology (SNAP) (A-T/N+; n = 14), Amyloid Only (A+T-N-; n = 24) and Probable AD (A+T+N+; n = 77) groups. Sparse canonical correlation analyses were employed to model spatially disjointed regions of association between MRI and 18FDG-PET data. These relationships were assessed at three combinations of time points -cross-sectionally, between baseline visits and between month 12 (M-12) follow-up visits, as well as longitudinally between baseline and M-12 follow-up.

RESULTS

In the SNAP group, spatially overlapping relationships between atrophy and hypometabolism were apparent in the bilateral temporal lobes when both modalities were assessed at the M-12 timepoint. Amyloid-Only subjects showed spatially discordant distributed atrophy-hypometabolism relationships at all time points assessed. In Probable AD subjects, local correlations were evident in the bilateral temporal lobes when both modalities were assessed at baseline and at M-12. Across groups, hypometabolism at baseline correlated with non-local, or distant, atrophy at M-12.

CONCLUSION

These results support the view that local concordance of atrophy and hypometabolism is the result of a tau-mediated process driving neurodegeneration.

Optimal deep brain stimulation sites and networks for stimulation of the fornix in Alzheimer's disease

Deep brain stimulation (DBS) to the fornix is an investigational treatment for patients with mild Alzheimer's Disease. Outcomes from randomized clinical trials have shown that cognitive function improved in some patients but deteriorated in others. This could be explained by variance in electrode placement leading to differential engagement of neural circuits. To investigate this, we performed a post-hoc analysis on a multi-center cohort of 46 patients with DBS to the fornix (NCT00658125, NCT01608061). Using normative structural and functional connectivity data, we found that stimulation of the circuit of Papez and stria terminalis robustly associated with cognitive improvement (R = 0.53, p < 0.001). On a local level, the optimal stimulation site resided at the direct interface between these structures (R = 0.48, p < 0.001). Finally, modulating specific distributed brain networks related to memory accounted for optimal outcomes (R = 0.48, p < 0.001). Findings were robust to multiple cross-validation designs and may define an optimal network target that could refine DBS surgery and programming.

The mean diffusivity of forceps minor is useful to distinguish amnestic mild cognitive impairment from mild cognitive impairment caused by cerebral small vessel disease

Objectives

In recent years, the desire to make a more fine-grained identification on mild cognitive impairment (MCI) has become apparent, the etiological diagnosis of MCI in particular. Nevertheless, new methods for the etiological diagnosis of MCI are currently insufficient. The objective of this study was to establish discriminative measures for amnestic mild cognitive impairment (a-MCI) and MCI caused by cerebral small vessel disease (CSVD).

Materials and methods

In total, 20 normal controls (NCs), 33 a-MCI patients, and 25 CSVD-MCI patients performed comprehensive neuropsychological assessments concerning global cognitive function and five cognitive domains as well as magnetic resonance imaging scan with diffusion tensor imaging (DTI). Diffusion parameters including fractional anisotropy and mean diffusivity of 20 major white matter metrics were obtained by ROI-based analyses. The neuropsychological tests and diffusion measurements were compared and binary logistic regression was used to identify the best differential indicator for the two MCI subgroups. The discriminating power was calculated by receiver operating characteristic analysis.

Results

Amnestic mild cognitive impairment group showed significant impairment in memory and language function, while CSVD-MCI group revealed more deficits in multi-cognitive domains of memory, language, attention and executive function than controls. Compared to the a-MCI, CSVD-MCI was significantly dysfunctional in the executive function. The CSVD-MCI group had decreased fractional anisotropy and increased mean diffusivity values throughout widespread white matter areas. CSVD-MCI presented more severe damage in the anterior thalamic radiation, forceps major, forceps minor and right inferior longitudinal fasciculus compared with a-MCI group. No significant neuropsychological tests were found in the binary logistic regression model, yet the DTI markers showed a higher discriminative power than the neuropsychological tests. The Stroop test errors had moderate potential (AUC = 0.747; sensitivity = 76.0%; specificity = 63.6%; P = 0.001; 95% CI: 0.617–0.877), and the mean diffusivity value of forceps minor demonstrated the highest predictive power to discriminate each MCI subtype (AUC = 0.815; sensitivity = 88.0%; specificity = 72.7%; P &lt; 0.001; 95% CI: 0.698–0.932).

Conclusion

The mean diffusivity of forceps minor may serve as an optimal indicator to differentiate between a-MCI and CSVD-MCI.

Alterations in resting-state functional connectivity associated to the age-related decline in time-based prospective memory

Time-based prospective memory (TBPM) is defined as the ability to remember to perform intended actions at a specific time in the future. TBPM is impaired in aging, and this decline has been associated with white-matter alterations within the superior fronto-occipital fasciculus. In the present study, we used resting-state functional magnetic resonance imaging from 22 healthy young (26 ± 5.2 years) and 23 older (63 ± 6.1 years) participants to investigate how age-related alterations in resting-state functional connectivity are related to TBPM performance, and whether these alterations are associated with the white-matter disruptions we have previously observed with diffusion tensor imaging. Whole-brain analyses revealed lower resting-state functional connectivity in older participants compared with younger ones, which in turn correlated with TBPM performance. These correlations were mainly located in the salience network and the parietal part of the frontoparietal network. Our findings suggest that resting-state functional connectivity alterations contribute to the age-related decline in TBPM.

The Parietal Lobe in Alzheimer’s Disease and Blindness

The progressive aging of the population will notably increase the burden of those diseases which leads to a disabling situation, such as Alzheimer’s disease (AD) and ophthalmological diseases that cause a visual impairment (VI). Eye diseases that cause a VI raise neuroplastic processes in the parietal lobe. Meanwhile, the aforementioned lobe suffers a severe decline throughout AD. From this perspective, diving deeper into the particularities of the parietal lobe is of paramount importance. In this article, we discuss the functions of the parietal lobe, review the parietal anatomical and pathophysiological peculiarities in AD, and also describe some of the changes in the parietal region that occur after VI. Although the alterations in the hippocampus and the temporal lobe have been well documented in AD, the alterations of the parietal lobe have been less thoroughly explored. Recent neuroimaging studies have revealed that some metabolic and perfusion impairments along with a reduction of the white and grey matter could take place in the parietal lobe during AD. Conversely, it has been speculated that blinding ocular diseases induce a remodeling of the parietal region which is observable through the improvement of the integration of multimodal stimuli and in the increase of the volume of this cortical region. Based on current findings concerning the parietal lobe in both pathologies, we hypothesize that the increased activity of the parietal lobe in people with VI may diminish the neurodegeneration of this brain region in those who are visually impaired by oculardiseases.

Associations of Social Isolation and Loneliness With Later Dementia

BACKGROUND AND OBJECTIVES

To investigate the independent associations of social isolation and loneliness with incident dementia and to explore the potential neurobiological mechanisms.

METHODS

We utilized the UK Biobank cohort to establish Cox proportional hazard models with social isolation and loneliness as separate exposures. Demographic (sex, age, and ethnicity), socioeconomic (education level, household income, and Townsend deprivation index), biological (body mass index, APOE genotype, diabetes, cancer, cardiovascular disease, and other), cognitive (speed of processing and visual memory), behavioral (current smoker, alcohol intake, and physical activity), and psychological (social isolation or loneliness, depressive symptoms, and neuroticism) factors measured at baseline were adjusted. Then, voxel-wise brainwide association analyses were used to identify gray matter volumes (GMVs) associated with social isolation and with loneliness. Partial least squares regression was performed to test the spatial correlation of GMV differences and gene expression using the Allen Human Brain Atlas.

RESULTS

We included 462,619 participants (mean age at baseline 57.0 years [SD 8.1]). With a mean follow-up of 11.7 years (SD 1.7), 4,998 developed all-cause dementia. Social isolation was associated with a 1.26-fold increased risk of dementia (95% CI, 1.15-1.37) independently of various risk factors including loneliness and depression (i.e., full adjustment). However, the fully adjusted hazard ratio for dementia related to loneliness was 1.04 (95% CI, 0.94-1.16) and 75% of this relationship was attributable to depressive symptoms. Structural MRI data were obtained from 32,263 participants (mean age 63.5 years [SD 7.5]). Socially isolated individuals had lower GMVs in temporal, frontal, and other (e.g., hippocampal) regions. Mediation analysis showed that the identified GMVs partly mediated the association between social isolation at baseline and cognitive function at follow-up. Social isolation-related lower GMVs were related to underexpression of genes that are downregulated in Alzheimer disease and to genes that are involved in mitochondrial dysfunction and oxidative phosphorylation.

DISCUSSION

Social isolation is a risk factor for dementia that is independent of loneliness and many other covariates. Social isolation-related brain structural differences coupled with different molecular functions also support the associations of social isolation with cognition and dementia. Social isolation may thus be an early indicator of an increased risk of dementia.

Structural progression of Alzheimer’s disease over decades: the MRI staging scheme

The chronological progression of brain atrophy over decades, from pre-symptomatic to dementia stages, has never been formally depicted in Alzheimer’s disease. This is mainly due to the lack of cohorts with long enough MRI follow-ups in cognitively unimpaired young participants at baseline. To describe a spatiotemporal atrophy staging of Alzheimer’s disease at the whole-brain level, we built extrapolated lifetime volumetric models of healthy and Alzheimer’s disease brain structures by combining multiple large-scale databases (n = 3512 quality controlled MRI from 9 cohorts of subjects covering the entire lifespan, including 415 MRI from ADNI1, ADNI2 and AIBL for Alzheimer’s disease patients). Then, we validated dynamic models based on cross-sectional data using external longitudinal data. Finally, we assessed the sequential divergence between normal aging and Alzheimer’s disease volumetric trajectories and described the following staging of brain atrophy progression in Alzheimer’s disease: (i) hippocampus and amygdala; (ii) middle temporal gyrus; (iii) entorhinal cortex, parahippocampal cortex and other temporal areas; (iv) striatum and thalamus and (v) middle frontal, cingular, parietal, insular cortices and pallidum. We concluded that this MRI scheme of atrophy progression in Alzheimer’s disease was close but did not entirely overlap with Braak staging of tauopathy, with a ‘reverse chronology’ between limbic and entorhinal stages. Alzheimer’s disease structural progression may be associated with local tau accumulation but may also be related to axonal degeneration in remote sites and other limbic-predominant associated proteinopathies.

Impact of long- and short-range fiber depletion on the cognitive deficits of fronto-temporal dementia

Recent studies suggest a framework where white-matter (WM) atrophy plays an important role in fronto-temporal dementia (FTD) pathophysiology. However, these studies often overlook the fact that WM tracts bridging different brain regions may have different vulnerabilities to the disease and the relative contribution of grey-matter (GM) atrophy to this WM model, resulting in a less comprehensive understanding of the relationship between clinical symptoms and pathology. Using a common factor analysis to extract a semantic and an executive factor, we aimed to test the relative contribution of WM and GM of specific tracts in predicting cognition in the Frontotemporal Lobar Degeneration Neuroimaging Initiative (FTLDNI). We found that semantic symptoms were mainly dependent on short-range WM fibre disruption, while damage to long-range WM fibres was preferentially associated to executive dysfunction with the GM contribution to cognition being predominant for local processing. These results support the importance of the disruption of specific WM tracts to the core cognitive symptoms associated with FTD. As large-scale WM tracts, which are particularly vulnerable to vascular disease, were highly associated with executive dysfunction, our findings highlight the importance of controlling for risk factors associated with deep WM disease, such as vascular risk factors, in patients with FTD in order not to potentiate underlying executive dysfunction.

Imaging Clinical Subtypes and Associated Brain Networks in Alzheimer’s Disease

Alzheimer’s disease (AD) does not present uniform symptoms or a uniform rate of progression in all cases. The classification of subtypes can be based on clinical symptoms or patterns of pathological brain alterations. Imaging techniques may allow for the identification of AD subtypes and their differentiation from other neurodegenerative diseases already at an early stage. In this review, the strengths and weaknesses of current clinical imaging methods are described. These include positron emission tomography (PET) to image cerebral glucose metabolism and pathological amyloid or tau deposits. Magnetic resonance imaging (MRI) is more widely available than PET. It provides information on structural or functional changes in brain networks and their relation to AD subtypes. Amyloid PET provides a very early marker of AD but does not distinguish between AD subtypes. Regional patterns of pathology related to AD subtypes are observed with tau and glucose PET, and eventually as atrophy patterns on MRI. Structural and functional network changes occur early in AD but have not yet provided diagnostic specificity.

Depressive symptoms in cognitively unimpaired older adults are associated with lower structural and functional integrity in a frontolimbic network

Subclinical depressive symptoms are associated with increased risk of Alzheimer's disease (AD), but the brain mechanisms underlying this relationship are still unclear. We aimed to provide a comprehensive overview of the brain substrates of subclinical depressive symptoms in cognitively unimpaired older adults using complementary multimodal neuroimaging data. We included cognitively unimpaired older adults from the baseline data of the primary cohort Age-Well (n = 135), and from the replication cohort ADNI (n = 252). In both cohorts, subclinical depressive symptoms were assessed using the 15-item version of the Geriatric Depression Scale; based on this scale, participants were classified as having depressive symptoms (>0) or not (0). Voxel-wise between-group comparisons were performed to highlight differences in gray matter volume, glucose metabolism and amyloid deposition; as well as white matter integrity (only available in Age-Well). Age-Well participants with subclinical depressive symptoms had lower gray matter volume in the hippocampus and lower white matter integrity in the fornix and the posterior parts of the cingulum and corpus callosum, compared to participants without symptoms. Hippocampal atrophy was recovered in ADNI, where participants with subclinical depressive symptoms also showed glucose hypometabolism in the hippocampus, amygdala, precuneus/posterior cingulate cortex, medial and dorsolateral prefrontal cortex, insula, and temporoparietal cortex. Subclinical depressive symptoms were not associated with brain amyloid deposition in either cohort. Subclinical depressive symptoms in ageing are linked with neurodegeneration biomarkers in the frontolimbic network including brain areas particularly sensitive to AD. The relationship between depressive symptoms and AD may be partly underpinned by neurodegeneration in common brain regions.

Going round in circles-The Papez circuit in Alzheimer's disease

The hippocampus is regarded as the pivotal structure for episodic memory symptoms associated with Alzheimer's disease (AD) pathophysiology. However, what is often overlooked is that the hippocampus is 'only' one part of a network of memory critical regions, the Papez circuit. Other Papez circuit regions are often regarded as less relevant for AD as they are thought to sit 'downstream' of the hippocampus. However, this notion is oversimplistic, and increasing evidence suggests that other Papez regions might be affected before or concurrently with the hippocampus. In addition, AD research has mostly focused on episodic memory deficits, whereas spatial navigation processes are also subserved by the Papez circuit with increasing evidence supporting its valuable potential as a diagnostic measure of incipient AD pathophysiology. In the current review, we take a step forward analysing recent evidence on the structural and functional integrity of the Papez circuit across AD disease stages. Specifically, we will review the integrity of specific Papez regions from at-genetic-risk (APOE4 carriers), to mild cognitive impairment (MCI), to dementia stage of sporadic AD and autosomal dominant AD (ADAD). We related those changes to episodic memory and spatial navigation/orientation deficits in AD. Finally, we provide an overview of how the Papez circuit is affected in AD diseases and their specific symptomology contributions. This overview strengthened the need for moving away from a hippocampal-centric view to a network approach on how the whole Papez circuit is affected in AD and contributes to its symptomology, informing future research and clinical approaches.

Cortical hypometabolism reflects local atrophy and tau pathology in symptomatic Alzheimer's disease

Posterior cortical hypometabolism measured with [18F]-Fluorodeoxyglucose (FDG)-PET is a well-known marker of Alzheimer's disease-related neurodegeneration, but its associations with underlying neuropathological processes are unclear. We assessed cross-sectionally the relative contributions of three potential mechanisms causing hypometabolism in the retrosplenial and inferior parietal cortices: local molecular (amyloid and tau) pathology and atrophy, distant factors including contributions from the degenerating medial temporal lobe or molecular pathology in functionally connected regions, and the presence of the apolipoprotein E (APOE) ε4 allele. Two hundred and thirty-two amyloid-positive cognitively impaired patients from two cohorts (University of California, San Francisco, UCSF, and Alzheimer's Disease Neuroimaging Initiative, ADNI) underwent MRI and PET with FDG, amyloid-PET using [11C]-Pittsburgh Compound B, [18F]-Florbetapir, or [18F]-Florbetaben, and [18F]-Flortaucipir tau-PET within one year. Standard uptake value ratios (SUVR) were calculated using tracer-specific reference regions. Regression analyses were run within cohorts to identify variables associated with retrosplenial or inferior parietal FDG SUVR. On average, ADNI patients were older and were less impaired than UCSF patients. Regional patterns of hypometabolism were similar between cohorts, though there were cohort differences in regional gray matter atrophy. Local cortical thickness and tau-PET (but not amyloid-PET) were independently associated with both retrosplenial and inferior parietal FDG SUVR (ΔR2 = .09 to .21) across cohorts in models that also included age and disease severity (local model). Including medial temporal lobe volume improved the retrosplenial FDG model in ADNI (ΔR2 = .04, p = .008) but not UCSF (ΔR2 < .01, p = .52), and did not improve the inferior parietal models (ΔR2s < .01, ps > .37). Interaction analyses revealed that medial temporal volume was more strongly associated with retrosplenial FDG SUVR at earlier disease stages (p = .06 in UCSF, p = .046 in ADNI). Exploratory analyses across the cortex confirmed overall associations between hypometabolism and local tau pathology and thickness and revealed associations between medial temporal degeneration and hypometabolism in retrosplenial, orbitofrontal, and anterior cingulate cortices. Finally, our data did not support hypotheses of a detrimental effect of pathology in connected regions or of an effect of the APOE ε4 allele in impaired participants. Overall, in two independent groups of patients at symptomatic stages of Alzheimer's disease, cortical hypometabolism mainly reflected structural neurodegeneration and tau, but not amyloid, pathology.

Fascicle- and Glucose-Specific Deterioration in White Matter Energy Supply in Alzheimer's Disease

BACKGROUND

White matter energy supply to oligodendrocytes and the axonal compartment is crucial for normal axonal function. Although gray matter glucose hypometabolism is extensively reported in Alzheimer's disease (AD), glucose and ketones, the brain's two main fuels, are rarely quantified in white matter in AD.

OBJECTIVE

Using a dual-tracer PET method combined with a fascicle-specific diffusion MRI approach, robust to white matter hyper intensities and crossing fibers, we aimed to quantify both glucose and ketone metabolism in specific white matter fascicles associated with mild cognitive impairment (MCI; n = 51) and AD (n = 13) compared to cognitively healthy age-matched controls (Controls; n = 14).

METHODS

Eight white matter fascicles of the limbic lobe and corpus callosum were extracted and analyzed into fascicle profiles of five sections. Glucose (18F-fluorodeoxyglucose) and ketone (11C-acetoacetate) uptake rates, corrected for partial volume effect, were calculated along each fascicle.

RESULTS

The only fascicle with significantly lower glucose uptake in AD compared to Controls was the left posterior cingulate segment of the cingulum (-22%; p = 0.016). Non-significantly lower glucose uptake in this fascicle was also observed in MCI. In contrast to glucose, ketone uptake was either unchanged or higher in sections of the fornix and parahippocampal segment of the cingulum in AD.

CONCLUSION

To our knowledge, this is the first report of brain fuel uptake calculated along white matter fascicles in humans. Energetic deterioration in white matter in AD appears to be specific to glucose and occurs first in the posterior cingulum.

Green tea consumption is associated with annual changes in hippocampal volumes: A longitudinal study in community-dwelling middle-aged and older Japanese individuals

BACKGROUND

To investigate the association between green tea consumption and the annual rate of change of gray matter (GM), white matter (WM), and hippocampal volumes in community-dwelling middle-aged and older Japanese individuals.

METHODS

A prospective cohort study with two years of follow-up was conducted as part of the National Institute for Longevity Sciences-Longitudinal Study of Aging (NILS-LSA) project. A total of 1693 participants (862 men and 831 women, aged 40-89 years) were included. Green tea consumption (mL/day) data were collected with a 3-day dietary record. Volumes of GM, WM, and the hippocampus were estimated by T1-weighted brain magnetic resonance imaging and FreeSurfer software. The GM ratio, WM ratio, and hippocampal ratio (HR) were calculated as the percentages of total intracranial volume, respectively.

RESULTS

The mean (SD) annual rate of change of hippocampal volume [(HR at baseline - HR at follow-up)/HR at baseline/follow-up years×100%] was 0.499 (1.128) (%). In the multivariable-adjusted general linear model, green tea consumption was negatively associated only with the annual rate of change of hippocampal volume (%) [β (95% CI) for each 1 mL/day increase in green tea consumption = -20.2E-5 (-35.0E-5 to -5.3E-5); P-value = 0.008]. No associations were observed for the annual rate of change of GM or WM volumes. The results remained significant when the analysis was limited to those with stable green tea consumption and were especially evident among individuals aged 65 years and older and among women.

CONCLUSIONS

In this study, higher green tea consumption was associated with less annual hippocampal atrophy, and each additional 100 mL/day of green tea intake was related to a reduction of approximately 5% in annual hippocampal atrophy. This association was especially evident among older individuals and among women. Further study in different settings is needed to confirm this association.

Graph Models of Pathology Spread in Alzheimer's Disease: An Alternative to Conventional Graph Theoretic Analysis

Background: Graph theory and connectomics are new techniques for uncovering disease-induced changes in the brain's structural network. Most prior studied have focused on network statistics as biomarkers of disease. However, an emerging body of work involves exploring how the network serves as a conduit for the propagation of disease factors in the brain and has successfully mapped the functional and pathological consequences of disease propagation. In Alzheimer's disease (AD), progressive deposition of misfolded proteins amyloid and tau is well-known to follow fiber projections, under a "prion-like" trans-neuronal transmission mechanism, through which misfolded proteins cascade along neuronal pathways, giving rise to network spread. Methods: In this review, we survey the state of the art in mathematical modeling of connectome-mediated pathology spread in AD. Then we address several open questions that are amenable to mathematically precise parsimonious modeling of pathophysiological processes, extrapolated to the whole brain. We specifically identify current formal models of how misfolded proteins are produced, aggregate, and disseminate in brain circuits, and attempt to understand how this process leads to stereotyped progression in Alzheimer's and other related diseases. Conclusion: This review serves to unify current efforts in modeling of AD progression that together have the potential to explain observed phenomena and serve as a test-bed for future hypothesis generation and testing in silico. Impact statement Graph theory is a powerful new approach that is transforming the study of brain processes. There do not exist many focused reviews of the subfield of graph modeling of how Alzheimer's and other dementias propagate within the brain network, and how these processes can be mapped mathematically. By providing timely and topical review of this subfield, we fill a critical gap in the community and present a unified view that can serve as an in silico test-bed for future hypothesis generation and testing. We also point to several open and unaddressed questions and controversies that future practitioners can tackle.

Metabolic and amyloid PET network reorganization in Alzheimer's disease: differential patterns and partial volume effects

Alzheimer’s disease (AD) is a neurodegenerative disorder, considered a disconnection syndrome with regional molecular pattern abnormalities quantifiable by the aid of PET imaging. Solutions for accurate quantification of network dysfunction are scarce. We evaluate the extent to which PET molecular markers reflect quantifiable network metrics derived through the graph theory framework and how partial volume effects (PVE)-correction (PVEc) affects these PET-derived metrics 75 AD patients and 126 cognitively normal older subjects (CN). Therefore our goal is twofold: 1) to evaluate the differential patterns of [¹⁸F]FDG- and [¹⁸F]AV45-PET data to depict AD pathology; and ii) to analyse the effects of PVEc on global uptake measures of [¹⁸F]FDG- and [¹⁸F]AV45-PET data and their derived covariance network reconstructions for differentiating between patients and normal older subjects. Network organization patterns were assessed using graph theory in terms of “degree”, “modularity”, and “efficiency”. PVEc evidenced effects on global uptake measures that are specific to either [¹⁸F]FDG- or [¹⁸F]AV45-PET, leading to increased statistical differences between the groups. PVEc was further shown to influence the topological characterization of PET-derived covariance brain networks, leading to an optimised characterization of network efficiency and modularisation. Partial-volume effects correction improves the interpretability of PET data in AD and leads to optimised characterization of network properties for organisation or disconnection.

Age-related differences in structural and functional prefrontal networks during a logical reasoning task

In logical reasoning, difficulties in inhibition of currently-held beliefs may lead to unwarranted conclusions, known as belief bias. Aging is associated with difficulties in inhibitory control, which may lead to deficits in inhibition of currently-held beliefs. No study to date, however, has investigated the underlying neural substrates of age-related differences in logical reasoning and the impact of belief load. The aim of the present study was to delineate age differences in brain activity during a syllogistic logical reasoning task while the believability load of logical inferences was manipulated. Twenty-nine, healthy, younger and thirty, healthy, older adults (males and females) completed a functional magnetic resonance imaging experiment in which they were asked to determine the logical validity of conclusions. Unlike younger adults, older adults engaged a large-scale network including anterior cingulate cortex and inferior frontal gyrus during conclusion stage. Our functional connectivity results suggest that while older adults engaged the anterior cingulate network to overcome their intuitive responses for believable inferences, the inferior frontal gyrus network contributed to higher control over responses during both believable and unbelievable conditions. Our functional results were further supported by structure-function-behavior analyses indicating the importance of cingulum bundle and uncinate fasciculus integrity in rejection of believable statements. These novel findings lend evidence for age-related differences in belief bias, with potentially important implications for decision making where currently-held beliefs and given assumptions are in conflict.

Verbal memory and hippocampal volume predict subsequent fornix microstructure in those at risk for Alzheimer's disease

While strong cross-sectional evidence supported the use of fornix microstructure as a marker for detecting Alzheimer’s disease (AD), longitudinal data remains inconclusive on the sequential nature of fornix microstructure abnormalities and AD progression. An unequivocal longitudinal relationship between fornix microstructure and markers of AD progression –memory impairment and hippocampal atrophy, must be established to validate fornix microstructure as a marker of AD progression. We included 115 participants from the Alzheimer’s Disease Neuroimaging Initiative across the non-demented AD spectrum— defined as those who had at least one AD risk marker at baseline (e.g., mild cognitive impairment (MCI) due to AD diagnosis, amyloid or ApoE4 positivity) and/or ‘cognitively normal individuals who converted to MCI due to AD or AD, with structural and diffusion tensor imaging scans at baseline and two years follow-up. Hippocampal volumes (HV), fractional anisotropy (FA) and mean diffusivity (MD) in the fornix were extracted. Memory was indexed via composite scores of verbal memory tests. Structural equation models tested the bidirectional cross-lagged effects of fornix microstructure, memory, and HV. Impaired memory and smaller HV at baseline significantly predicted worse fornix microstructure (decreased FA and increased MD) two years later. Baseline fornix microstructure was not associated with subsequent changes in memory and HV. Fornix microstructure is compromised likely at a later stage, where significant decline in memory and hippocampal atrophy have occurred. This limits the utility of fornix microstructure in the early detection of AD. Our findings inform the possible pathophysiology and refined the use of AD neural markers.

Data-driven FDG-PET subtypes of Alzheimer's disease-related neurodegeneration

BACKGROUND

Previous research has described distinct subtypes of Alzheimer's disease (AD) based on the differences in regional patterns of brain atrophy on MRI. We conducted a data-driven exploration of distinct AD neurodegeneration subtypes using FDG-PET as a sensitive molecular imaging marker of neurodegenerative processes.

METHODS

Hierarchical clustering of voxel-wise FDG-PET data from 177 amyloid-positive patients with AD dementia enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI) was used to identify distinct hypometabolic subtypes of AD, which were then further characterized with respect to clinical and biomarker characteristics. We then classified FDG-PET scans of 217 amyloid-positive patients with mild cognitive impairment ("prodromal AD") according to the identified subtypes and studied their domain-specific cognitive trajectories and progression to dementia over a follow-up interval of up to 72 months.

RESULTS

Three main hypometabolic subtypes were identified: (i) "typical" (48.6%), showing a classic posterior temporo-parietal hypometabolic pattern; (ii) "limbic-predominant" (44.6%), characterized by old age and a memory-predominant cognitive profile; and (iii) a relatively rare "cortical-predominant" subtype (6.8%) characterized by younger age and more severe executive dysfunction. Subtypes classified in the prodromal AD sample demonstrated similar subtype characteristics as in the AD dementia sample and further showed differential courses of cognitive decline.

CONCLUSIONS

These findings complement recent research efforts on MRI-based identification of distinct AD atrophy subtypes and may provide a potentially more sensitive molecular imaging tool for early detection and characterization of AD-related neurodegeneration variants at prodromal disease stages.

Relationship between the disrupted topological efficiency of the structural brain connectome and glucose hypometabolism in normal aging

Normal aging is accompanied by structural degeneration and glucose hypometabolism in the human brain. However, the relationship between structural network disconnections and hypometabolism in normal aging remains largely unknown. In the present study, by combining MRI and PET techniques, we investigated the metabolic mechanism of the structural brain connectome and its relationship with normal aging in a cross-sectional, community-based cohort of 42 cognitively normal elderly individuals aged 57-84 years. The structural connectome was constructed based on diffusion MRI tractography, and the network efficiency metrics were quantified using graph theory analyses. FDG-PET scanning was performed to evaluate the glucose metabolic level in the cortical regions of the individuals. The results of this study demonstrated that both network efficiency and cortical metabolism decrease with age (both p < 0.05). In the subregions of the bilateral thalamus, significant correlations between nodal efficiency and cortical metabolism could be observed across subjects. Individual-level analyses indicated that brain regions with higher nodal efficiency tend to exhibit higher metabolic levels, implying a tight coupling between nodal efficiency and glucose metabolism (r = 0.56, p = 1.15 × 10^-21). Moreover, efficiency-metabolism coupling coefficient significantly increased with age (r = 0.44, p = 0.0046). Finally, the main findings were also reproducible in the ADNI dataset. Together, our results demonstrate a close coupling between structural brain connectivity and cortical metabolism in normal elderly individuals and provide new insight that improve the present understanding of the metabolic mechanisms of structural brain disconnections in normal aging.

Distinct Interplay Between Atrophy and Hypometabolism in Alzheimer's Versus Semantic Dementia

Multimodal neuroimaging analyses offer additional information beyond that provided by each neuroimaging modality. Thus, direct comparisons and correlations between neuroimaging modalities allow revealing disease-specific topographic relationships. Here, we compared the topographic discrepancies between atrophy and hypometabolism in two neurodegenerative diseases characterized by distinct pathological processes, namely Alzheimer's disease (AD) versus semantic dementia (SD), to unravel their specific influence on local and global brain structure-function relationships. We found that intermodality topographic discrepancies clearly distinguished the two patient groups: AD showed marked discrepancies between both alterations, with greater hypometabolism than atrophy in large posterior associative neocortical regions, while SD showed more topographic consistency between atrophy and hypometabolism across brain regions. These findings likely reflect the multiple pathologies versus the relatively unitary pathological process underlying AD versus SD respectively. Our results evidence that multimodal neuroimaging-derived indexes can provide clinically relevant information to discriminate the two diseases, and potentially reveal distinct neuropathological processes.

Gaussian Graphical Models Reveal Inter-Modal and Inter-Regional Conditional Dependencies of Brain Alterations in Alzheimer's Disease

Alzheimer's disease (AD) is characterized by a sequence of pathological changes, which are commonly assessed in vivo using various brain imaging modalities such as magnetic resonance imaging (MRI) and positron emission tomography (PET). Currently, the most approaches to analyze statistical associations between regions and imaging modalities rely on Pearson correlation or linear regression models. However, these models are prone to spurious correlations arising from uninformative shared variance and multicollinearity. Notably, there are no appropriate multivariate statistical models available that can easily integrate dozens of multicollinear variables derived from such data, being able to utilize the additional information provided from the combination of data sources. Gaussian graphical models (GGMs) can estimate the conditional dependency from given data, which is conceptually expected to closely reflect the underlying causal relationships between various variables. Hence, we applied GGMs to assess multimodal regional brain alterations in AD. We obtained data from N = 972 subjects from the Alzheimer's Disease Neuroimaging Initiative. The mean amyloid load (AV45-PET), glucose metabolism (FDG-PET), and gray matter volume (MRI) were calculated for each of the 108 cortical and subcortical brain regions. GGMs were estimated using a Bayesian framework for the combined multimodal data and the resulted conditional dependency networks were compared to classical covariance networks based on Pearson correlation. Additionally, graph-theoretical network statistics were calculated to determine network alterations associated with disease status. The resulting conditional dependency matrices were much sparser (≈10% density) than Pearson correlation matrices (≈50% density). Within imaging modalities, conditional dependency networks yielded clusters connecting anatomically adjacent regions. For the associations between different modalities, only few region-specific connections were detected. Network measures such as small-world coefficient were significantly altered across diagnostic groups, with a biphasic u-shape trajectory, i.e., increased small-world coefficient in early mild cognitive impairment (MCI), similar values in late MCI, and decreased values in AD dementia patients compared to cognitively normal controls. In conclusion, GGMs removed commonly shared variance among multimodal measures of regional brain alterations in MCI and AD, and yielded sparser matrices compared to correlation networks based on the Pearson coefficient. Therefore, GGMs may be used as alternative to thresholding-approaches typically applied to correlation networks to obtain the most informative relations between variables.

The heterogeneous functional architecture of the posteromedial cortex is associated with selective functional connectivity differences in Alzheimer's disease

The posteromedial cortex (PMC) is a key region involved in the development and progression of Alzheimer's disease (AD). Previous studies have demonstrated a heterogenous functional architecture of the region that is composed of discrete functional modules reflecting a complex pattern of functional connectivity. However, little is understood about the mechanisms underpinning this complex network architecture in neurodegenerative disease, and the differential vulnerability of connectivity-based subdivisions in the PMC to AD pathogenesis. Using a data-driven approach, we applied a constrained independent component analysis (ICA) on healthy adults from the Human Connectome Project to characterise the local functional connectivity patterns within the PMC, and its unique whole-brain functional connectivity. These distinct connectivity profiles were subsequently quantified in the Alzheimer's Disease Neuroimaging Initiative study, to examine functional connectivity differences in AD patients and cognitively normal (CN) participants, as well as the entire AD pathological spectrum. Our findings revealed decreased functional connectivity in the anterior precuneus, dorsal posterior cingulate cortex (PCC), and the central precuneus in AD patients compared to CN participants. Functional abnormalities in the dorsal PCC and central precuneus were also related to amyloid burden and volumetric hippocampal loss. Across the entire AD spectrum, functional connectivity of the central precuneus was associated with disease severity and specific deficits in memory and executive function. These findings provide new evidence showing that the PMC is selectively impacted in AD, with prominent network failures of the dorsal PCC and central precuneus underpinning the neurodegenerative and cognitive dysfunctions associated with the disease.

Medial temporal lobe connectivity and its associations with cognition in early Alzheimer's disease

Human episodic memory critically depends on subregions of the medial temporal lobe, which are part of functional brain systems such as the anterior-temporal and the posterior-medial system. Here we analysed how Alzheimer's pathology affects functional connectivity within these systems. Data from 256 amyloid-β-negative cognitively unimpaired, 103 amyloid-β-positive cognitively unimpaired, and 83 amyloid-β-positive individuals with mild cognitive impairment were analysed. Amyloid-β and tau pathology were measured using the CSF amyloid-β42/40 ratio and phosphorylated tau, respectively. We found that amyloid-β-positive cognitively unimpaired individuals were mainly characterized by decreased functional connectivity between the medial temporal lobe and regions in the anterior-temporal system, most prominently between left perirhinal/entorhinal cortices and medial prefrontal cortex. Furthermore, correlation analysis in this group revealed decreasing functional connectivity between bilateral perirhinal/entorhinal cortices, anterior hippocampus and posterior-medial regions with increasing levels of phosphorylated tau. The amyloid-β-positive individuals with mild cognitive impairment mostly exhibited reduced connectivity between the medial temporal lobe and posterior-medial regions, predominantly between the anterior hippocampus and posterior cingulate cortex. In addition, they showed hyperconnectivity within the medial temporal lobe and its immediate proximity. Lower medial temporal-cortical functional connectivity networks resulting from the group comparisons of cognitively unimpaired individuals were associated with reduced memory performance and more rapid longitudinal memory decline as shown by linear mixed-effects regression analysis. Finally, we found that reduced medial temporal-cortical connectivity in mildly cognitively impaired individuals was related to reduced entorhinal thickness and white matter integrity of the parahippocampal cingulum and the fornix. No such relationships were found in cognitively unimpaired individuals. In conclusion, our findings show that the earliest changes in preclinical Alzheimer's disease might involve decreased connectivity within the anterior-temporal system, and early changes in connectivity might be related to memory impairment, but not to structural changes. With disease progression and increased tau pathology, medial temporal functional connectivity with posterior-medial regions seems to be increasingly impaired. In individuals with mild cognitive impairment, reduced functional connectivity is associated with structural brain changes as well as the emergence of locally increased connectivity patterns. Thus, functional connectivity between the medial temporal lobe and the anterior-temporal and posterior-medial system could serve as stage-specific functional markers in early Alzheimer's disease.

Functional Connectivity Alterations of the Temporal Lobe and Hippocampus in Semantic Dementia and Alzheimer's Disease

BACKGROUND

Semantic memory impairments in semantic dementia are attributed to atrophy and functional disruption of the anterior temporal lobes. In contrast, the posterior medial temporal neurodegeneration found in Alzheimer's disease is associated with episodic memory disturbance. The two dementia subtypes share hippocampal deterioration, despite a relatively spared episodic memory in semantic dementia.

OBJECTIVE

To unravel mutual and divergent functional alterations in Alzheimer's disease and semantic dementia, we assessed functional connectivity between temporal lobe regions in Alzheimer's disease (n = 16), semantic dementia (n = 23), and healthy controls (n = 17).

METHODS

In an exploratory study, we used a functional parcellation of the temporal cortex to extract time series from 66 regions for correlation analysis.

RESULTS

Apart from differing connections between Alzheimer's disease and semantic dementia that yielded reduced functional connectivity, we identified a common pathway between the right anterior temporal lobe and the right orbitofrontal cortex in both dementia subtypes. This disconnectivity might be related to social knowledge deficits as part of semantic memory decline. However, such interpretations are preferably made in a holistic context of disease-specific semantic impairments and functional connectivity changes.

CONCLUSION

Despite a major limitation owed to unbalanced databases between study groups, this study provides a preliminary picture of the brain's functional disconnectivity in Alzheimer's disease and semantic dementia. Future studies are needed to replicate findings of a common pathway with consistent diagnostic criteria and neuropsychological evaluation, balanced designs, and matched data MRI acquisition procedures.

A Study on PHF-Tau Network Effected by Apolipoprotein E4

Apolipoprotein E 4 Allele (APOE 4) is an important factors in Mild cognitive impairment (MCI) and Alzheimer's disease(AD). It plays a primary role in abnormal modification of aggregated Tau protein-paired helical filaments Tau (PHF-Tau). In this study, 143 subjects with PHF-Tau PET were divided into 2 groups (APOE 4 carriers and noncarriers). The measurements of the PHF-Tau network properties and resilient were calculated for 2 group networks respectively. APOE 4 carriers group showed significant differences in all the network properties in the results. We also found significant differences of betweenness centrality in some brain regions for APOE 4 carriers. Moreover, the APOE 4 carriers showed less resilient to targeted or random node failure. Our results indicated that the effects of APOE 4 may lead to abnormalities of PHF-Tau protein network. These findings may be particularly helpful in uncovering the pathophysiology underlying the cognitive dysfunction in MCI patients.

The accuracy of hippocampal volumetry and glucose metabolism for the diagnosis of patients with suspected Alzheimer's disease, using automatic quantitative clinical tools

The hippocampus is one of the earliest sites involved in the pathology of Alzheimer's disease (AD). Therefore, we specifically investigated the sensitivity and specificity of hippocampal volume and glucose metabolism in patients being evaluated for AD, using automated quantitative tools (NeuroQuant - magnetic resonance imaging [MRI] and Scenium - positron emission tomography [PET]) and clinical evaluation.This retrospective study included adult patients over the age of 45 years with suspected AD, who had undergone fluorodeoxyglucose positron emission tomography-computed tomography (FDG-PET-CT) and MRI. FDG-PET-CT images were analyzed both qualitatively and quantitatively. In quantitative volumetric MRI analysis, the percentage of the total intracranial volume of each brain region, as well as the total hippocampal volume, were considered in comparison to an age-adjusted percentile. The remaining brain regions were compared between groups according to the final diagnosis.Thirty-eight patients were included in this study. After a mean follow-up period of 23 ± 11 months, the final diagnosis for 16 patients was AD or high-risk mild cognitive impairment (MCI). Out of the 16 patients, 8 patients were women, and the average age of all patients was 69.38 ± 10.98 years. Among the remaining 22 patients enrolled in the study, 14 were women, and the average age was 67.50 ± 11.60 years; a diagnosis of AD was initially excluded, but the patients may have low-risk MCI. Qualitative FDG-PET-CT analysis showed greater accuracy (0.87), sensitivity (0.76), and negative predictive value (0.77), when compared to quantitative PET analysis, hippocampal MRI volumetry, and specificity. The positive predictive value of FDG-PET-CT was similar to the MRI value.The performance of FDG-PET-CT qualitative analysis was significantly more effective compared to MRI volumetry. At least in part, this observation could corroborate the sequential hypothesis of AD pathophysiology, which posits that functional changes (synaptic dysfunction) precede structural changes (atrophy).

No relationship between fornix and cingulum degradation and within-network decreases in functional connectivity in prodromal Alzheimer's disease

INTRODUCTION

The earliest changes in the brain due to Alzheimer's disease are associated with the neural networks related to memory function. We investigated changes in functional and structural connectivity among regions that support memory function in prodromal Alzheimer's disease, i.e., during the mild cognitive impairment (MCI) stage.

METHODS

Twenty-three older healthy controls and 25 adults with MCI underwent multimodal MRI scanning. Limbic white matter tracts-the fornix, parahippocampal cingulum, retrosplenial cingulum, subgenual cingulum and uncinate fasciculus-were reconstructed in ExploreDTI using constrained spherical deconvolution-based tractography. Using a network-of-interest approach, resting-state functional connectivity time-series correlations among sub-parcellations of the default mode and limbic networks, the hippocampus and the thalamus were calculated in Conn.

ANALYSIS

Controlling for age, education, and gender between group linear regressions of five diffusion-weighted measures and of resting state connectivity measures were performed per hemisphere. FDR-corrections were performed within each class of measures. Correlations of within-network Fisher Z-transformed correlation coefficients and the mean diffusivity per tract were performed. Whole-brain graph theory measures of cluster coefficient and average path length were inspecting using the resting state data.

RESULTS & CONCLUSION

MCI-related changes in white matter structure were found in the fornix, left parahippocampal cingulum, left retrosplenial cingulum and left subgenual cingulum. Functional connectivity decreases were observed in the MCI group within the DMN-a sub-network, between the hippocampus and sub-areas -a and -c of the DMN, between DMN-c and DMN-a, and, in the right hemisphere only between DMN-c and both the thalamus and limbic-a. No relationships between white matter tract 'integrity' (mean diffusivity) and within sub-network functional connectivity were found. Graph theory revealed that changes in the MCI group was mostly restricted to diminished between-neighbour connections of the hippocampi and of nodes within DMN-a and DMN-b.

Increased white matter diffusivity associated with phantom limb pain

Background

We utilized diffusion tensor imaging (DTI) to evaluate the cerebral white matter changes that are associated with phantom limb pain in patients with unilateral arm amputation. It was anticipated that this would complement previous research in which we had shown that changes in cerebral blood volume were associated with the cerebral pain network.

Methods

Ten patients with phantom limb pain due to unilateral arm amputation and sixteen healthy age-matched controls were enrolled. The intensity of phantom limb pain was measured by the visual analogue scale (VAS) and depressive mood was assessed by the Hamilton depression rating scale. Diffusion tensor-derived parameters, including fractional anisotropy, mean diffusivity, axial diffusivity (AD), and radial diffusivity (RD), were computed from the DTI.

Results

Compared with controls, the cases had alterations in the cerebral white matter as a consequence of phantom limb pain, manifesting a higher AD of white matter in both hemispheres symmetrically after adjusting for individual depressive moods. In addition, there were associations between the RD of white matter and VAS scores primarily in the hemispheres related to the missing hand and in the corpus callosum.

Conclusions

The phantom limb pain after unilateral arm amputation induced plasticity in the white matter. We conclude that loss of white matter integrity, particularly in the hemisphere connected with the missing hand, is significantly correlated with phantom limb pain.

The Influence of Cerebrospinal Fluid Abnormalities and APOE 4 on PHF-Tau Protein: Evidence From Voxel Analysis and Graph Theory

Mild cognitive impairment (MCI) is a transitional state between the cognitive changes in normal aging and Alzheimer’s disease (AD), which induces abnormalities in specific brain regions. Previous studies showed that paired helical filaments Tau (PHF-Tau) protein is a potential pathogenic protein which may cause abnormal brain function and structure in MCI and AD patients. However, the understanding of the PHF-Tau protein network in MCI patients is limited. In this study, 225 subjects with PHF-Tau Positron Emission Tomography (PET) images were divided into four groups based on whether they carried Apolipoprotein E ε4 (APOE 4) or abnormal cerebrospinal fluid Total-Tau (CSF T-Tau). They are two important pathogenic factors that might cause cognitive function impairment. The four groups were: individuals harboring CSF T-Tau pathology but no APOE 4 (APOE 4−T+); APOE 4 carriers with normal CSF T-Tau (APOE 4+T−); APOE 4 carriers with abnormal CSF T-Tau (APOE 4+T+); and APOE 4 noncarriers with abnormal CSF T-Tau (APOE 4−T−). We explored the topological organization of PHF-Tau networks in these four groups and calculated five kinds of network properties: clustering coefficient, shortest path length, Q value of modularity, nodal centrality and degree. Our findings showed that compared with APOE 4−T− group, the other three groups showed different alterations in the clustering coefficient, shortest path length, Q value of modularity, nodal centrality and degree. Simultaneously, voxel-level analysis was conducted and the results showed that compared with APOE 4−T− group, the other three groups were found increased PHF-Tau distribution in some brain regions. For APOE 4+T+ group, positive correlation was found between the value of PHF-Tau distribution in altered regions and Functional Assessment Questionnaire (FAQ) score. Our results indicated that the effects of APOE 4 and abnormal CSF T-Tau may induce abnormalities of PHF-Tau protein and APOE 4 has a greater impact on PHF-Tau than abnormal CSF T-Tau. Our results may be particularly helpful in uncovering the pathophysiology underlying the cognitive dysfunction in MCI patients.

ASAF: altered spontaneous activity fingerprinting in Alzheimer's disease based on multisite fMRI

Several monocentric studies have noted alterations in spontaneous brain activity in Alzheimer's disease (AD), although there is no consensus on the altered amplitude of low-frequency fluctuations in AD patients. The main aim of the present study was to identify a reliable and reproducible abnormal brain activity pattern in AD. The amplitude of local brain activity (AM), which can provide fast mapping of spontaneous brain activity across the whole brain, was evaluated based on multisite rs-fMRI data for 688 subjects (215 normal controls (NCs), 221 amnestic mild cognitive impairment (aMCI) 252 AD). Two-sample t-tests were used to detect group differences between AD patients and NCs from the same site. Differences in the AM maps were statistically analyzed via the Stouffer's meta-analysis. Consistent regions of lower spontaneous brain activity in the default mode network and increased activity in the bilateral hippocampus/parahippocampus, thalamus, caudate nucleus, orbital part of the middle frontal gyrus and left fusiform were observed in the AD patients compared with those in NCs. Significant correlations (P < 0.05, Bonferroni corrected) between the normalized amplitude index and Mini-Mental State Examination scores were found in the identified brain regions, which indicates that the altered brain activity was associated with cognitive decline in the patients. Multivariate analysis and leave-one-site-out cross-validation led to a 78.49% prediction accuracy for single-patient classification. The altered activity patterns of the identified brain regions were largely correlated with the FDG-PET results from another independent study. These results emphasized the impaired brain activity to provide a robust and reproducible imaging signature of AD.

Studying the Manifold Structure of Alzheimer's Disease: A Deep Learning Approach Using Convolutional Autoencoders

Many classical machine learning techniques have been used to explore Alzheimer's disease (AD), evolving from image decomposition techniques such as principal component analysis toward higher complexity, non-linear decomposition algorithms. With the arrival of the deep learning paradigm, it has become possible to extract high-level abstract features directly from MRI images that internally describe the distribution of data in low-dimensional manifolds. In this work, we try a new exploratory data analysis of AD based on deep convolutional autoencoders. We aim at finding links between cognitive symptoms and the underlying neurodegeneration process by fusing the information of neuropsychological test outcomes, diagnoses, and other clinical data with the imaging features extracted solely via a data-driven decomposition of MRI. The distribution of the extracted features in different combinations is then analyzed and visualized using regression and classification analysis, and the influence of each coordinate of the autoencoder manifold over the brain is estimated. The imaging-derived markers could then predict clinical variables with correlations above 0.6 in the case of neuropsychological evaluation variables such as the MMSE or the ADAS11 scores, achieving a classification accuracy over 80% for the diagnosis of AD.

Multimodal Neuroimaging in Alzheimer's Disease: Early Diagnosis, Physiopathological Mechanisms, and Impact of Lifestyle

Over the last ten years, we have conducted research in Alzheimer's disease (AD) using multimodal neuroimaging techniques to improve diagnosis, further our understanding of the pathological mechanisms underlying the disease, and support the development of innovative non-pharmacological preventive strategies. Our works emphasized the interest of hippocampal subfield volumetry in early diagnosis and the need for further development in this field including optimization, standardization, and automatization of the techniques. Also, we conducted several studies in cognitively intact at-risk elderly (e.g., subjective cognitive decline patients and APOE4 carriers) to better identify biomarkers associated with increased risk of developing AD. Regarding the physiopathological mechanisms, specific multimodal neuroimaging techniques allowed us to highlight the relevance of diaschisis, the mismatch between neurodegeneration and local Aβ deposition and the regional variation in the mechanisms underlying structural or functional alterations. Further works integrating other biomarkers known to play a role in the physiopathology of AD (tau, TDP-43, inflammation, etc.) in a longitudinal design would be useful to get a comprehensive understanding of their relative role, sequence, and causal relationships. Our works also highlighted the relevance of functional connectivity in further understanding the specificity of cognitive deficits in AD and how connectivity differentially influences the propagation of the different AD biomarkers. Finally, we conducted several studies on the links between lifestyle factors and neuroimaging biomarkers to unravel mechanisms of reserve. Further efforts are needed to better understand which lifestyle factor, or combination of factors, impact on AD pathology, and when, to help translating our knowledge to training programs that might prevent or delay brain and cognitive changes leading to AD dementia.

Medial Temporal Lobe Disconnection and Hyperexcitability Across Alzheimer's Disease Stages

 The posteromedial cortex (PMC) and medial temporal lobes (MTL) are two brain regions particularly vulnerable in Alzheimer’s disease (AD). We have reviewed the spatiotemporal patterns of amyloid-β and tau accumulation, local MTL functional alterations and MTL-PMC network reconfiguration, and propose a model to relate these elements to each other. Functional and structural MTL-PMC disconnection happen concomitant with amyloid-β plaques and neurofibrillary tau accumulation within these same regions. Ongoing disconnection is accompanied by dysfunctional intrinsic local MTL circuit hyperexcitability, which exacerbates across distinct clinical stages of AD. Our overarching model proposes a sequence of events relating the spatiotemporal patterns of amyloid-β and tau accumulation to MTL-PMC disconnection and local MTL hyperexcitability. We hypothesize that cortical PMC amyloid-β pathology induces long-range information processing deficits through functional and structural MTL-PMC dysconnectivity at early disease stages, which in turn drives local MTL circuit hyperexcitability. Intrinsic local MTL circuit hyperexcitability subsequently accelerates local age-related tau deposition, facilitating tau spread from the MTL to the PMC, eventually resulting in extensive structural degeneration of white and grey matter as the disease advances. We hope that the present model may inform future longitudinal studies needed to test the proposed sequence of events.

Amyloid burden accelerates white matter degradation in cognitively normal elderly individuals

Alterations in parietal and temporal white matter microstructure derived from diffusion tensor imaging occur in preclinical and clinical Alzheimer's disease. Amyloid beta (Aβ) deposition and such white matter alterations are two pathological hallmarks of Alzheimer's disease. However, the relationship between these pathologies is not yet understood, partly since conventional diffusion MRI methods cannot distinguish between cellular and extracellular processes. Thus, we studied Aβ-associated longitudinal diffusion MRI changes in Aβ-positive (N = 21) and Aβ-negative (N = 51) cognitively normal elderly obtained from the Alzheimer's Disease Neuroimaging Initiative dataset using linear mixed models. Aβ-positivity was based on Alzheimer's Disease Neuroimaging Initiative amyloid-PET recommendations using a standardized uptake value ratio cut-off of 1.11. We used free-water imaging to distinguish cellular and extracellular changes. We found that Aβ-positive subjects had increased baseline right uncinate fasciculus free-water fraction (FW), associated with worse baseline Alzheimer's disease assessment scale scores. Furthermore, Aβ-positive subjects showed faster decrease in fractional anisotropy (FW-corrected) in the right uncinate fasciculus and faster age-dependent right inferior longitudinal fasciculus FW increases over time. Right inferior longitudinal fasciculus FW increases were associated with greater memory decline. Importantly, these results remained significant after controlling for gray and white matter volume and hippocampal volume. This is the first study to illustrate the influence of Aβ burden on early longitudinal (in addition to baseline) white matter changes in cognitively normal elderly individuals at-risk of Alzheimer's disease, thus underscoring the importance of longitudinal studies in assessing microstructural alterations in individuals at risk of Alzheimer's disease prior to symptoms onset.