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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.

Cognitive reserve (CR) is known to modulate the clinical features of Alzheimer's disease (AD). This concept may be critical for the development of non-pharmacological interventions able to slow down patients' cognitive decline in the absence of disease-modifying treatments. We aimed at identifying the neurobiological substrates of CR (i.e., neural reserve) over the transition between normal aging and AD, by assessing the underlying brain networks and their topological properties. A cohort of 154 participants (n=68 with AD, n=61 with amnestic mild cognitive impairment (aMCI), and 25 healthy subjects) underwent resting-state functional MRI and neuropsychological testing. Within each group, participants were classified as having high or low CR, and functional connectivity measures were compared, within group, between high and low CR individuals. Network-based statistics and topological network properties derived from graph theory were explored. Connectivity differences between high and low CR were evident only for aMCI patients, with participants with high CR showing a significant increase of connectivity in a network involving mainly fronto-parietal nodes. Conversely, they showed significantly decreased connectivity in a network involving fronto-temporo-cerebellar nodes. Consistently, changes to topological measures were observed in either direction, and were associated with measures of global cognitive function. These findings support the hypothesis that CR impacts on neurodegenerative process in the early phase of AD only. In addition, they fit with the existence of a "neural reserve", characterized by specific neural networks and their efficiency. It remains to be demonstrated whether interventions later in life can modulate this "neural reserve".

This longitudinal study investigates the modifications in structure and function occurring to typical Alzheimer's disease (AD) brains over a 2-year follow-up, from pre-dementia stages of disease, with the aim of identifying biomarkers of prognostic value. Thirty-one patients with amnestic mild cognitive impairment were recruited and followed-up with clinical, neuropsychological, and MRI assessments. Patients were retrospectively classified as AD Converters or Non-Converters, and the data compared between groups. Cross-sectional MRI data at baseline, assessing volume and functional connectivity abnormalities, confirmed previous findings, showing a more severe pattern of regional grey matter atrophy and default-mode network disconnection in Converters than in Non-Converters. Longitudinally, Converters showed more grey matter atrophy in the frontotemporal areas, accompanied by increased connectivity in the precuneus. Discriminant analysis revealed that functional connectivity of the precuneus within the default mode network at baseline is the parameter able to correctly classify patients in Converters and Non-Converters with high sensitivity, specificity, and accuracy.

Graph-theoretical approaches have become a popular way to model brain data collected using magnetic resonance imaging (MRI), both from the structural and the functional perspectives. In structural networks, tract-based mapping allows to model different aspects of brain structures by means of the specific characteristics of the different MRI modalities. However, there has been little effort to join the information carried by each modality and to understand what level of common variance is shown in these data. In this paper, we proposed a combined approach based on graph theory and factor analysis to model magnetization transfer and microstructural properties in 18 relapsing remitting multiple sclerosis (RRMS) patients and 17 healthy controls. After defining the common factors and outlining their relationships with MRI data, we evaluated between-group differences using global and local graph measures. The results showed that one common factor describes brain structures in terms of myelin and global integrity, and such factor is able to highlight specific between-group differences.