Investigating White Matter Lesion Load, Intrinsic Functional Connectivity, and Cognitive Abilities in Older Adults

Changes to the while matter of the brain disrupt neural communication between spatially distributed brain regions and are associated with cognitive changes in later life. While approximately 95% of older adults experience these brain changes, not everyone who has significant white matter damage displays cognitive impairment. Few studies have investigated the association between white matter changes and cognition in the context of functional brain network integrity. This study used a data-driven, multivariate analytical model to investigate intrinsic functional connectivity patterns associated with individual variability in white matter lesion load as related to fluid and crystallized intelligence in a sample of healthy older adults (n = 84). Several primary findings were noted. First, a reliable pattern emerged associating whole-brain resting-state functional connectivity with individual variability in measures of white matter lesion load, as indexed by total white matter lesion volume and number of lesions. Secondly, white matter lesion load was associated with increased network disintegration and dedifferentiation. Specifically, lower white matter lesion load was associated with greater within- versus between-network connectivity. Higher white matter lesion load was associated with greater between-network connectivity compared to within. These associations between intrinsic functional connectivity and white matter lesion load were not reliably associated with crystallized and fluid intelligence performance. These results suggest that changes to the white matter of the brain in typically aging older adults are characterized by increased functional brain network dedifferentiation. The findings highlight the role of white matter lesion load in altering the functional network architecture of the brain

Comparison of ApoE-related brain connectivity differences in EMCI and normal aging populations: an fMRI study

In this study, we used resting-state functional magnetic resonance imaging (fMRI) scans from subjects with early mild cognitive impairment (EMCI) and control subjects to study functional network connectivity. The scans were acquired by the Alzheimer's Disease Neuroscience Initiative (ADNI). We used genetic data from the ADNI database to further subdivide the EMCI and control groups into genotype groups with or without the ApoE4 allele. ROI-to-ROI resting-state functional connectivity was measured using Freesurfer and the Functional Connectivity Toolbox for Matlab (CONN). In our analysis, we compared whole-brain ROI connectivity strength and ROI-to-ROI functional network connectivity strength between EMCI, control and genotype subject groups. We found that the ROI network properties were disrupted in EMCI and ApoE4-containing groups. Notably, we show that (1) EMCI disrupts functional connectivity strength in many areas; (2) the ApoE4 allele disrupts functional connectivity strength in similar areas to EMCI; and (3) the differences in functional connectivity between groups shows a multifactor contribution to functional network dysfunction along the trajectory leading to dementia

Functional Resting State Connectivity in Individuals At-Risk for Alzheimer\u27s Disease

Resting state functional magnetic resonance imaging studies have examined the connectivity between the hippocampus (HIPP) and the posterior cingulate (PC) in individuals with Alzheimer\u27s disease (AD), mild cognitive impairment (MCI), and younger individuals at risk for AD. The present study aimed to examine the functional connectivity between these two memory structures and targets of AD neurodegeneration in cognitively intact elders at risk for AD (positive for ApolipoE protein (ε4) and family history of dementia), MCI, and healthy controls. Seeds and regions of interest were defined in the bilateral hippocampus and posterior cingulate, and the time courses were cross-correlated to generate a value of functional connectivity between two structures for comparisons across groups. Results indicate the presence of greater functional connectivity between the left HIPP and PC in healthy elders at risk compared to patients with MCI and healthy controls and a general reduction in functional connectivity between bilateral HIPP and PC in patients with MCI. This marker of increased functional connectivity, during the resting state of the brain, found in cognitively intact elders at risk compared to cognitively intact controls and symptomatic patients with MCI might be an important diagnostic tool to identify those most vulnerable for the development of AD

Functional Magnetic Resonance Imaging of Semantic Memory as a Presymptomatic Biomarker of Alzheimer’s Disease Risk

Extensive research efforts have been directed toward strategies for predicting risk of developing Alzheimer\u27s disease (AD) prior to the appearance of observable symptoms. Existing approaches for early detection of AD vary in terms of their efficacy, invasiveness, and ease of implementation. Several non-invasive magnetic resonance imaging strategies have been developed for predicting decline in cognitively healthy older adults. This review will survey a number of studies, beginning with the development of a famous name discrimination task used to identify neural regions that participate in semantic memory retrieval and to test predictions of several key theories of the role of the hippocampus in memory. This task has revealed medial temporal and neocortical contributions to recent and remote memory retrieval, and it has been used to demonstrate compensatory neural recruitment in older adults, apolipoprotein E ε4 carriers, and amnestic mild cognitive impairment patients. Recently, we have also found that the famous name discrimination task provides predictive value for forecasting episodic memory decline among asymptomatic older adults. Other studies investigating the predictive value of semantic memory tasks will also be presented. We suggest several advantages associated with the use of semantic processing tasks, particularly those based on person identification, in comparison to episodic memory tasks to study AD risk. Future directions for research and potential clinical uses of semantic memory paradigms are also discussed. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease

Structural and Functional Brain Connectivity in Middle-Aged Carriers of Risk Alleles for Alzheimer\u27s Disease

Single nucleotide polymorphisms (SNPs) in APOE, COMT, BDNF, and KIBRA have been associated with age-related memory performance and executive functioning as well as risk for Alzheimer’s disease (AD). The purpose of the present investigation was to characterize differences in brain functional and structural integrity associated with these SNPs as potential endophenotypes of age-related cognitive decline. I focused my investigation on healthy, cognitively normal middle-aged adults, as disentangling the early effects of healthy versus pathological aging in this group may aid early detection and prevention of AD. The aims of the study were 1) to characterize SNP-related differences in functional connectivity within two resting state networks (RSNs; default mode network [DMN] and executive control network [ECN]) associated with memory and executive functioning, respectively; 2) to identify differences in the white matter (WM) microstructural integrity of tracts underlying these RSNs; and 3) to characterize genotype differences in the graph properties of an integrated functional-structural network. Participants (age 40-60, N = 150) underwent resting state functional magnetic resonance imaging (rs-fMRI), diffusion tensor imaging (DTI), and genotyping. Independent components analysis (ICA) was used to derive RSNs, while probabilistic tractography was performed to characterize tracts connecting RSN subregions. A technique known as functional-by-structural hierarchical (FSH) mapping was used to create the integrated, whole brain functional-structural network, or resting state structural connectome (rsSC). I found that BDNF risk allele carriers had lower functional connectivity within the DMN, while KIBRA risk allele carriers had poorer WM microstructural integrity in tracts underlying the DMN and ECN. In addition to these differences in the connectivity of specific RSNs, I found significant impairments in the global and local topology of the rsSC across all evaluated SNPs. Collectively, these findings suggest that integrating multiple neuroimaging modalities and using graph theoretical analysis may reveal network-level vulnerabilities that may serve as biomarkers of age-related cognitive decline in middle age, decades before the onset of overt cognitive impairment

Default mode resting-state functional connectivity of the aging brain

The term functional connectivity is used to describe which parts of the brain work together on a process, and might aid the understanding of how the processing systems in the human brain are fundamentally organised. The default mode network (DMN) is a constellation of cortical structures that has shown remarkable reliability as a resting-state network(RSN). It has often been referred to as a task-negative network, because it typically exhibits amplified activation patterns during rest. Numerous studies have documented DMN alterations in various clinical conditions, including mild cognitive impairment and Alzheimer’s disease. However, little is known about the impact of normal aging on this network. The present study investigates age–differences in DMN functional connectivity and further, whether the effects of age are modulated by the allelic variation of the alipoprotein E-gene, APOE. Based on current theories of cognitive aging and the few existing previous studies on restingstate patterns and APOE, we have two hypotheses: 1) an elevated co-activation in the DMN with increasing age, and 2) different effects for ε4-carriers compared to non-carriers in the MTL structures, including the hippocampus. We tested these hypotheses on resting-state functional magnetic resonance imaging (fMRI) data from 182 healthy participants aged 20-78 years, including 63 carriers of the ε4-allele. Using a combination of independent component analysis (ICA) and dual-regression, we document regionally specific escalations in DMN synchronicity with increased age, especially in frontal brain areas. Additionally, we observed a moderate negative effect of the ε4-allele in the posterior cingulate cortex (PCC) of the posterior parts of the DMN, indicating lower co-activity in carriers compared to non-carriers in areas spanning core parts of the DMN. These findings are discussed in light of theories of cognitive aging, and we argue that the amplified DMN functional connectivity with age is indicative of an age-related decrease in neural differentiation manifested as decreased decoupling between task-negative and task-positive brain networks during rest

Dissociating Alzheimer’s Disease from Amnestic Mild Cognitive Impairment using Time-Frequency Based EEG Neurometrics

This work explores the utility of using magnitude (ERSP), phase angle (ITPC), and cross-frequency coupling (PAC) indices derived from electroencephalogram (EEG) recording using spectral decomposition as unique biomarkers of Alzheimer’s Disease (AD) and amnestic mild cognitive impairment (aMCI), respectively. The experimental protocol was a visual oddball discrimination task conducted during a brief (approximately 20 minute) recording session. Participants were 60 older adults from an outpatient memory clinic diagnosed with either aMCI (n=29; M=73.0; SD=9.32) or AD (n=31; M=78.29; SD=8.28) according to NIA-AA criteria. Results indicate that ITPC values differ significantly between AD and MCI groups. Findings contribute to a growing body of literature seeking to document illness-related abnormalities in time-frequency EEG signatures that may serve as reliable indicators of the pathophysiological processes underlying the cognitive deficits observed in AD and aMCI-afflicted populations

Cognitive-Motor Integration In Normal Aging And Preclinical Alzheimer's Disease: Neural Correlates And Early Detection

The objectives of the studies included in this dissertation were to characterize how the ability to integrate cognition into action is disrupted by both normal and pathological aging, to evaluate the effectiveness of kinematic measures in discriminating between individuals who are and are not at increased Alzheimer’s disease (AD) risk, and to examine the structural and functional neural correlates of cognitive-motor impairment in individuals at increased AD risk. The underlying hypothesis, based on previous research, is that measuring visuomotor integration under conditions that place demands on visual-spatial and cognitive-motor processing may provide an effective behavioural means for the early detection of brain alterations associated with AD risk. To this end, the first study involved testing participants both with and without AD risk factors on visuomotor tasks using a dual-touchscreen tablet. Comparisons between high AD risk participants and both young and old healthy control groups revealed significant performance disruptions in at-risk participants in the most cognitively demanding task. Furthermore, a stepwise discriminant analysis was able to distinguish between high and low AD risk participants with a classification accuracy of 86.4%. Based on the prediction that the impairments observed in high AD risk participants reflect disruption to the intricate reciprocal communication between hippocampal, parietal, and frontal brain regions required to successfully prepare and update complex reaching movements, the second and third studies were designed to examine the underlying structural and functional connectivity associated with cognitive-motor performance. Young adult and both low AD risk and high AD risk older adult participants underwent anatomical, diffusion-weighted, and resting-state functional connectivity scans. These data revealed significant age-related declines in white matter integrity that were more pronounced in the high AD risk group. Decreased functional connectivity in the default mode network (DMN) was also found in high AD risk participants. Furthermore, measures of white matter integrity and resting-state functional connectivity with DMN seed-regions were significantly correlated with task performance. These data support our hypothesis that disease-related disruptions in visuomotor control are associated with identifiable brain alterations, and thus behavioural assessments incorporating both cognition and action together may be useful in identifying individuals at increased AD risk

Univariate and multivariate pattern analysis of preterm subjects: a multimodal neuroimaging study

Background: Widespread lasting functional connectivity (FC) and brain volume changes in cortices and subcortices after premature birth have been researched in recent studies. However, the relationship remains unclear between spontaneously slow blood oxygen dependent level (BOLD) fluctuations and gray matter volume (GMV) changes in specific brain areas, such as temporal insular cortices, and whether classification methods based on MRI could be successfully applied to the identification of preterm individuals. In this thesis I hypothesized that in prematurely born adults 1. Ongoing neural excitability and brain activity, as estimated by regional functional connectivity of resting state functional MRI (rs-fMRI) is accompanied with altered low-frequency fluctuations and neonatal complications; 2. Altered regional functional connectivity is connected with superimposed cerebral structural reductions; and 3. multivariate neuroanatomical and functional brain patterns could be treated as features to identify preterm subjects from term subjects individually. Methods: To investigate these hypotheses, the principal results of structural alterations were measured with voxel-based morphometry (VBM), while rs-fMRI outcomes were estimated with amplitude of low-frequency fluctuations (ALFF) in analysis with ninety-four very preterm/very low birth weight (VP/VLBW) and ninety-two full-term (FT) born young adults. Results: The results of the thesis support the hypotheses by showing that, in univariate results, first in VP/VLBW grownups, ALFF was decreased in the left lateral temporal cortices no matter with global signal regression, and this reduction was closely associated with neonatal complications and cognitive variables. Second overlapped brain regions were found between reduced ALFF and reduced brain volumes in the left temporal cortices, and positively associated with each other, demonstrating a potential relationship between VBM and ALFF in this brain area. In multimodal multivariate pattern recognition analysis (MVPA), the gray matter volume (GMV) classifier displayed a higher accuracy (80.7%) contrast with the ALFF classifier (77.4%). The late fusion of GMV and ALFF did not outperform single GMV modality classification by reaching 80.4% accuracy. Moderator analysis from both rs-fMRI and structural MRI (sMRI) uncovered that the neuro-prematurity performance was predominantly determined by neonatal complications. Conclusions: In conclusion, these outcomes exhibit the long term effects of premature labour on lateral temporal cortices, which changed in both ongoing BOLD fluctuations and decreased cerebral structural volumes. This thesis further provided evidence that multivariate pattern analysis such as support vector machine (SVM) may identify imaging-based biomarkers and reliably detect signatures of preterm birth