Alzheimer' Disease as a Disconnection Syndrome?

This paper reviews the growing amount of evidence supporting the hypothesis that Alzheimer's disease includes a disconnection syndrome. This evidence came mainly from neuropathological, electrophysiological, and neuroimaging studies. Moreover, a few recent neuropsychological studies have also explored the effects of a disconnection between cerebral areas on cognitive functioning. Finally, and more generally, the contribution of this interpretation to the understanding of Alzheimer's disease cognitive deficits is considere

Green Chemistry for the Transformation of Chlorinated Wastes: Catalytic Hydrodechlorination on Pd-Ni and Pd-Fe Bimetallic Catalysts Supported on SiO 2

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Endocarditis after Use of Tongue Scraper

We explored the neural substrate of anosognosia for cognitive impairment in Alzheimer's disease (AD). Two hundred nine patients with mild to moderate dementia and their caregivers assessed patients' cognitive impairment by answering a structured questionnaire. Subjects rated 13 cognitive domains as not impaired or associated with mild, moderate, severe, or very severe difficulties, and a sum score was calculated. Two measures of anosognosia were derived. A patient's self assessment, unconfounded by objective measurements of cognitive deficits such as dementia severity and episodic memory impairment, provided an estimate of impaired self-evaluative judgment about cognition in AD. Impaired self-evaluation was related to a decrease in brain metabolism measured with 18F-2-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) in orbital prefrontal cortex and in medial temporal structures. In a cognitive model of anosognosia, medial temporal dysfunction might impair a comparison mechanism between current information on cognition and personal knowledge. Hypoactivity in orbitofrontal cortex may not allow AD patients to update the qualitative judgment associated with their impaired cognitive abilities. Caregivers perceived greater cognitive impairments than patients did. The discrepancy score between caregiver's and patient's evaluations, an other measure of anosognosia, was negatively related to metabolic activity located in the temporoparietal junction, consistent with an impairment of self-referential processes and perspective taking in AD

Damage to the frontal aslant tract accounts for visuo-constructive deficits in Alzheimer's disease

The frontal aslant tract (FAT) has been described as a bundle connecting the Broca's area to the supplementary motor area (SMA) and the pre-SMA in both hemispheres. The functional properties of this tract and its role in degenerative dementia, such as Alzheimer's disease (AD), still need to be fully clarified. The aim of this study was to explore the microstructural integrity of the FAT in patients with AD and its potential relationship with cognitive functioning. Twenty-three patients with AD and 25 healthy subjects (HS) were enrolled. All subjects underwent cognitive and MRI examination. MRI, including diffusion sequences, was used for probabilistic tractography analysis. We reconstructed individual FATs bilaterally and assessed their microstructural integrity using fractional anisotropy (FA), computed as both mean tract value and voxel-wise using SPM-8. Mean FA values were then used to test for correlations with cognitive measures. Mean tract FA and voxel-wise analyses revealed that patients with AD, compared to HS, had decreased FA in the FAT bilaterally. In addition, positive associations were found between FA in the FATs and patients' performance at tests for constructional praxis and visuospatial logical reasoning. The present results reveal a bilateral damage of FAT in AD patients. The association between FATs' microscopic abnormalities and constructive abilities fits well with the knowledge of a functional involvement of SMA and pre-SMA in movement sequences when executing constructive praxis tasks. The FAT is an associative bundle critically involved in the network sub-serving constructional praxis in patients with AD

Locating Temporal Functional Dynamics of Visual Short-Term Memory Binding using Graph Modular Dirichlet Energy

Visual short-term memory binding tasks are a promising early marker for Alzheimer's disease (AD). To uncover functional deficits of AD in these tasks it is meaningful to first study unimpaired brain function. Electroencephalogram recordings were obtained from encoding and maintenance periods of tasks performed by healthy young volunteers. We probe the task's transient physiological underpinnings by contrasting shape only (Shape) and shape-colour binding (Bind) conditions, displayed in the left and right sides of the screen, separately. Particularly, we introduce and implement a novel technique named Modular Dirichlet Energy (MDE) which allows robust and flexible analysis of the functional network with unprecedented temporal precision. We find that connectivity in the Bind condition is less integrated with the global network than in the Shape condition in occipital and frontal modules during the encoding period of the right screen condition. Using MDE we are able to discern driving effects in the occipital module between 100-140ms, coinciding with the P100 visually evoked potential, followed by a driving effect in the frontal module between 140-180ms, suggesting that the differences found constitute an information processing difference between these modules. This provides temporally precise information over a heterogeneous population in promising tasks for the detection of AD

Disrupted Small-World Brain Networks in Moderate Alzheimer's Disease: A Resting-State fMRI Study

The small-world organization has been hypothesized to reflect a balance between local processing and global integration in the human brain. Previous multimodal imaging studies have consistently demonstrated that the topological architecture of the brain network is disrupted in Alzheimer's disease (AD). However, these studies have reported inconsistent results regarding the topological properties of brain alterations in AD. One potential explanation for these inconsistent results lies with the diverse homogeneity and distinct progressive stages of the AD involved in these studies, which are thought to be critical factors that might affect the results. We investigated the topological properties of brain functional networks derived from resting functional magnetic resonance imaging (fMRI) of carefully selected moderate AD patients and normal controls (NCs). Our results showed that the topological properties were found to be disrupted in AD patients, which showing increased local efficiency but decreased global efficiency. We found that the altered brain regions are mainly located in the default mode network, the temporal lobe and certain subcortical regions that are closely associated with the neuropathological changes in AD. Of note, our exploratory study revealed that the ApoE genotype modulates brain network properties, especially in AD patients

Reorganization of Functional Networks in Mild Cognitive Impairment

Whether the balance between integration and segregation of information in the brain is damaged in Mild Cognitive Impairment (MCI) subjects is still a matter of debate. Here we characterize the functional network architecture of MCI subjects by means of complex networks analysis. Magnetoencephalograms (MEG) time series obtained during a memory task were evaluated by synchronization likelihood (SL), to quantify the statistical dependence between MEG signals and to obtain the functional networks. Graphs from MCI subjects show an enhancement of the strength of connections, together with an increase in the outreach parameter, suggesting that memory processing in MCI subjects is associated with higher energy expenditure and a tendency toward random structure, which breaks the balance between integration and segregation. All features are reproduced by an evolutionary network model that simulates the degenerative process of a healthy functional network to that associated with MCI. Due to the high rate of conversion from MCI to Alzheimer Disease (AD), these results show that the analysis of functional networks could be an appropriate tool for the early detection of both MCI and AD

Network Analysis of Intrinsic Functional Brain Connectivity in Alzheimer's Disease

Functional brain networks detected in task-free (“resting-state”) functional magnetic resonance imaging (fMRI) have a small-world architecture that reflects a robust functional organization of the brain. Here, we examined whether this functional organization is disrupted in Alzheimer's disease (AD). Task-free fMRI data from 21 AD subjects and 18 age-matched controls were obtained. Wavelet analysis was applied to the fMRI data to compute frequency-dependent correlation matrices. Correlation matrices were thresholded to create 90-node undirected-graphs of functional brain networks. Small-world metrics (characteristic path length and clustering coefficient) were computed using graph analytical methods. In the low frequency interval 0.01 to 0.05 Hz, functional brain networks in controls showed small-world organization of brain activity, characterized by a high clustering coefficient and a low characteristic path length. In contrast, functional brain networks in AD showed loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01), indicative of disrupted local connectivity. Clustering coefficients for the left and right hippocampus were significantly lower (p<0.01) in the AD group compared to the control group. Furthermore, the clustering coefficient distinguished AD participants from the controls with a sensitivity of 72% and specificity of 78%. Our study provides new evidence that there is disrupted organization of functional brain networks in AD. Small-world metrics can characterize the functional organization of the brain in AD, and our findings further suggest that these network measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging

Functional Disconnection and Compensation in Mild Cognitive Impairment: Evidence from DLPFC Connectivity Using Resting-State fMRI

The known regional abnormality of the dorsolateral prefrontal cortex (DLPFC) and its role in various neural circuits in mild cognitive impairment (MCI) has given prominence to its importance in studies on the disconnection associated with MCI. The purpose of the current study was to examine the DLPFC functional connectivity patterns during rest in MCI patients and the impact of regional grey matter (GM) atrophy on the functional results. Structural and functional MRI data were collected from 14 MCI patients and 14 age, gender-matched healthy controls. We found that both the bilateral DLPFC showed reduced functional connectivity with the inferior parietal lobule (IPL), superior/medial frontal gyrus and sub-cortical regions (e.g., thalamus, putamen) in MCI patients when compared with healthy controls. Moreover, the DLPFC connectivity with the IPL and thalamus significantly correlated with the cognitive performance of patients as measured by mini-mental state examination (MMSE), clock drawing test (CDT), and California verbal learning test (CVLT) scores. When taking GM atrophy as covariates, these results were approximately consistent with those without correction, although there may be a decrease in the statistical power. These results suggest that the DLPFC disconnections may be the substrates of cognitive impairments in MCI patients. In addition, we also found enhanced functional connectivity between the left DLPFC and the right prefrontal cortex in MCI patients. This is consistent with previous findings of MCI-related increased activation during cognitive tasks, and may represent a compensatory mechanism in MCI patients. Together, the present study demonstrated the coexistence of functional disconnection and compensation in MCI patients using DLPFC functional connectivity analysis, and thus might provide insights into biological mechanism of the disease

Altered Connectivity Pattern of Hubs in Default-Mode Network with Alzheimer's Disease: An Granger Causality Modeling Approach

Background: Evidences from normal subjects suggest that the default-mode network (DMN) has posterior cingulate cortex (PCC), medial prefrontal cortex (MPFC) and inferior parietal cortex (IPC) as its hubs; meanwhile, these DMN nodes are often found to be abnormally recruited in Alzheimer’s disease (AD) patients. The issues on how these hubs interact to each other, with the rest nodes of the DMN and the altered pattern of hubs with respect to AD, are still on going discussion for eventual final clarification. Principal Findings: To address these issues, we investigated the causal influences between any pair of nodes within the DMN using Granger causality analysis and graph-theoretic methods on resting-state fMRI data of 12 young subjects, 16 old normal controls and 15 AD patients respectively. We found that: (1) PCC/MPFC/IPC, especially the PCC, showed the widest and distinctive causal effects on the DMN dynamics in young group; (2) the pattern of DMN hubs was abnormal in AD patients compared to old control: MPFC and IPC had obvious causal interaction disruption with other nodes; the PCC showed outstanding performance for it was the only region having causal relation with all other nodes significantly; (3) the altered relation between hubs and other DMN nodes held potential as a noninvasive biomarker of AD. Conclusions: Our study, to the best of our knowledge, is the first to support the hub configuration of the DMN from the perspective of causal relationship, and reveal abnormal pattern of the DMN hubs in AD. Findings from young subject