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Nowadays, increasing longevity associated with declining cerebral nervous system functions, suggests the need for continued development of new imaging contrast mechanisms to support the differential diagnosis of age-related decline. In our previous papers, we developed a new imaging contrast metrics derived from anomalous diffusion signal representation and obtained from diffusion-weighted (DW) data collected by varying diffusion gradient strengths. Recently, we highlighted that the new metrics, named γ-metrics, depended on the local inhomogeneity due to differences in magnetic susceptibility between tissues and diffusion compartments in young healthy subjects, thus providing information about myelin orientation and iron content within cerebral regions. The major structural modifications occurring in brain aging are myelinated fibers damage in nerve fibers and iron accumulation in gray matter nuclei. Therefore, we investigated the potential of γ-metrics in relation to other conventional diffusion metrics such as DTI, DKI and NODDI in detecting age-related structural changes in white matter (WM) and subcortical gray matter (scGM). DW-images were acquired in 32 healthy subjects, adults and elderly (age range 20-77 years) using 3.0T and 12 b-values up to 5000 s/mm 2 . Association between diffusion metrics and subjects' age was assessed using linear regression. A decline in mean γ (Mγ) in the scGM and a complementary increase in radial γ (γ ⊥ ) in frontal WM, genu of corpus callosum and anterior corona radiata with advancing age were found. We suggested that the increase in γ⊥ might reflect declined myelin density, and Mγ decrease might mirror iron accumulation. An increase in D // and a decrease in the orientation dispersion index (ODI) were associated with axonal loss in the pyramidal tracts, while their inverted trends within the thalamus were thought to be linked to reduced architectural complexity of nerve fibers. γ-metrics together with conventional diffusion-metrics can more comprehensively characterize the complex mechanisms underlining age-related changes than conventional diffusion techniques alone., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Microstructural imaging and connectomics are two research areas that hold great potential for investigating brain structure and function. Combining these two approaches can lead to a better and more complete characterization of the brain as a network. The aim of this work is characterizing the connectome from a novel perspective using the myelination measure given by the g-ratio. The g-ratio is the ratio of the inner to the outer diameters of a myelinated axon, whose aggregated value can now be estimated in vivo using MRI. In two different datasets of healthy subjects, we reconstructed the structural connectome and then used the g-ratio estimated from diffusion and magnetization transfer data to characterize the network structure. Significant characteristics of g-ratio weighted graphs emerged. First, the g-ratio distribution across the edges of the graph did not show the power-law distribution observed using the number of streamlines as a weight. Second, connections involving regions related to motor and sensory functions were the highest in myelin content. We also observed significant differences in terms of the hub structure and the rich-club organization suggesting that connections involving hub regions present higher myelination than peripheral connections. Taken together, these findings offer a characterization of g-ratio distribution across the connectome in healthy subjects and lay the foundations for further investigating plasticity and pathology using a similar approach., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Memory loss is one of the first symptoms of typical Alzheimer's disease (AD), for which there are no effective therapies available. The precuneus (PC) has been recently emphasized as a key area for the memory impairment observed in early AD, likely due to disconnection mechanisms within large-scale networks such as the default mode network (DMN). Using a multimodal approach we investigated in a two-week, randomized, sham-controlled, double-blinded trial the effects of high-frequency repetitive transcranial magnetic stimulation (rTMS) of the PC on cognition, as measured by the Alzheimer Disease Cooperative Study Preclinical Alzheimer Cognitive Composite in 14 patients with early AD (7 females). TMS combined with electroencephalography (TMS-EEG) was used to detect changes in brain connectivity. We found that rTMS of the PC induced a selective improvement in episodic memory, but not in other cognitive domains. Analysis of TMS-EEG signal revealed an increase of neural activity in patients' PC, an enhancement of brain oscillations in the beta band and a modification of functional connections between the PC and medial frontal areas within the DMN. Our findings show that high-frequency rTMS of the PC is a promising, non-invasive treatment for memory dysfunction in patients at early stages of AD. This clinical improvement is accompanied by modulation of brain connectivity, consistently with the pathophysiological model of brain disconnection in AD., (Copyright © 2017. Published by Elsevier Inc.)

Multivariate pattern analysis and statistical machine learning techniques are attracting increasing interest from the neuroimaging community. Researchers and clinicians are also increasingly interested in the study of functional-connectivity patterns of brains at rest and how these relations might change in conditions like Alzheimer's disease or clinical depression. In this study we investigate the efficacy of a specific multivariate statistical machine learning technique to perform patient stratification from functional-connectivity patterns of brains at rest. Whilst the majority of previous approaches to this problem have employed support vector machines (SVMs) we investigate the performance of Bayesian Gaussian process logistic regression (GP-LR) models with linear and non-linear covariance functions. GP-LR models can be interpreted as a Bayesian probabilistic analogue to kernel SVM classifiers. However, GP-LR methods confer a number of benefits over kernel SVMs. Whilst SVMs only return a binary class label prediction, GP-LR, being a probabilistic model, provides a principled estimate of the probability of class membership. Class probability estimates are a measure of the confidence the model has in its predictions, such a confidence score may be extremely useful in the clinical setting. Additionally, if miss-classification costs are not symmetric, thresholds can be set to achieve either strong specificity or sensitivity scores. Since GP-LR models are Bayesian, computationally expensive cross-validation hyper-parameter grid-search methods can be avoided. We apply these methods to a sample of 77 subjects; 27 with a diagnosis of probable AD, 50 with a diagnosis of a-MCI and a control sample of 39. All subjects underwent a MRI examination at 3T to obtain a 7minute and 20second resting state scan. Our results support the hypothesis that GP-LR models can be effective at performing patient stratification: the implemented model achieves 75% accuracy disambiguating healthy subjects from subjects with amnesic mild cognitive impairment and 97% accuracy disambiguating amnesic mild cognitive impairment subjects from those with Alzheimer's disease, accuracies are estimated using a held-out test set. Both results are significant at the 1% level., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Preliminary studies, based on a region-of-interest approach, suggest that quantitative magnetization transfer (qMT), an extension of magnetization transfer imaging, provides complementary information to conventional magnetic resonance imaging (MRI) in the characterisation of Alzheimer's disease (AD). The aim of this study was to extend these findings to the whole brain, using a voxel-wise approach. We recruited 19AD patients and 11 healthy subjects (HS). All subjects had an MRI acquisition at 3.0T including a T(1)-weighted volume, 12 MT-weighted volumes for qMT, and data for computing T(1) and B(1) maps. The T(1)-weighted volumes were processed to yield grey matter (GM) volumetric maps, while the other sequences were used to compute qMT parametric maps of the whole brain. qMT maps were warped to standard space and smoothed, and subsequently compared between groups. Of all the qMT parameters considered, only the forward exchange rate, RM(0)(B), showed significant group differences. These images were therefore retained for the multimodal statistical analysis, designed to locate brain regions of RM(0)(B) differences between AD and HS groups, adjusting for local GM atrophy. Widespread areas of reduced RM(0)(B) were found in AD patients, mainly located in the hippocampus, in the temporal lobe, in the posterior cingulate and in the parietal cortex. These results indicate that, among qMT parameters, RM(0)(B) is the most sensitive to AD pathology. This quantity is altered in the hippocampus of patients with AD (as found by previous works) but also in other brain areas, that PET studies have highlighted as involved with both, reduced glucose metabolism and amyloid β deposition. RM(0)(B) might reflect, through the measurement of the efficiency of MT exchange, some information with a specific pathological counterpart. Given previous evidence of a strict relationship between RM(0)(B) and intracellular pH, an intriguing speculation is that our findings might reflect metabolic changes related to mitochondrial dysfunction, which has been proposed as a contributor to neurodegeneration in AD., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Previous studies suggest that the clinical manifestations of Alzheimer's disease (AD) are not only associated with regional gray matter damage but also with abnormal functional integration of different brain regions by disconnection mechanisms. A measure of anatomical connectivity (anatomical connectivity mapping or ACM) can be obtained by initiating diffusion tractography streamlines from all parenchymal voxels and then counting the number of streamlines passing through each voxel of the brain. In order to assess the potential of this parameter for the study of disconnection in AD, we computed it in a group of patients with AD (N=9), in 16 patients with amnestic mild cognitive impairment (a-MCI, which is considered the prodromal stage of AD) and in 12 healthy volunteers. All subjects had an MRI scan at 3T, and diffusion MRI data were analyzed to obtain fractional anisotropy (FA) and ACM. Two types of ACM maps, absolute count (ac-ACM) and normalized by brain size count (nc-ACM), were obtained. No between group differences in FA surviving correction for multiple comparison were found, while areas of both decreased (in the supramarginal gyrus) and increased (in the putamen) ACM were found in patients with AD. Similar results were obtained with ac-ACM and nc-ACM. ACM of the supramarginal gyrus was strongly associated with measures of short-term memory in healthy subjects. This study shows that ACM provides information that is complementary to that offered by FA and appears to be more sensitive than FA to brain changes in patients with AD. The increased ACM in the putamen was unexpected. Given the nature of ACM, an increase of this parameter may reflect a change in any of the areas connected to it. One intriguing possibility is that this increase of ACM in AD patients might reflect processes of brain plasticity driven by cholinesterase inhibitors., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Obstructive sleep apnea (OSA) is accompanied by neurocognitive impairment, likely mediated by injury to various brain regions. We evaluated brain morphological changes in patients with OSA and their relationship to neuropsychological and oximetric data. Sixteen patients affected by moderate-severe OSA (age: 55.8±6.7 years, 13 males) and fourteen control subjects (age: 57.6±5.1 years, 9 males) underwent 3.0 Tesla brain magnetic resonance imaging (MRI) and neuropsychological testing evaluating short- and long-term memory, executive functions, language, attention, praxia and non-verbal learning. Volumetric segmentation of cortical and subcortical structures and voxel-based morphometry (VBM) were performed. Patients and controls differed significantly in Rey Auditory-Verbal Learning test (immediate and delayed recall), Stroop test and Digit span backward scores. Volumes of cortical gray matter (GM), right hippocampus, right and left caudate were smaller in patients compared to controls, with also brain parenchymal fraction (a normalized measure of cerebral atrophy) approaching statistical significance. Differences remained significant after controlling for comorbidities (hypertension, diabetes, smoking, hypercholesterolemia). VBM analysis showed regions of decreased GM volume in right and left hippocampus and within more lateral temporal areas in patients with OSA. Our findings indicate that the significant cognitive impairment seen in patients with moderate-severe OSA is associated with brain tissue damage in regions involved in several cognitive tasks. We conclude that OSA can increase brain susceptibility to the effects of aging and other clinical and pathological occurrences., (Copyright © 2010 Elsevier Inc. All rights reserved.)

We combined bifocal transcranial magnetic stimulation (TMS) and diffusion tensor imaging (DTI) tractography to investigate in humans the contribution of connections originating from different parietal areas in planning of different reaching to grasp movements. TMS experiments revealed that in the left hemisphere functional connectivity between the primary motor cortex (M1) and a portion of the angular gyrus (AG) close to the caudal intraparietal sulcus was activated during early preparation of reaching and grasping movements only when the movement was made with a whole hand grasp (WHG) towards objects in contralateral space. In contrast, a different pathway, linking M1 with a part of the supramarginal gyrus (SMG) close to the anterior intraparietal sulcus, was sensitive only to the type of grasp required (precision grasping) but not to the position of the object in space. A triple coil experiment revealed that inactivation of the ventral premotor area (PMv) by continuous theta burst stimulation interfered with some of these interactions. Anatomical DTI tractography revealed that AG and SMG are strongly connected with PMv and with M1 by different bundles of the superior longitudinal fasciculus (SLF). These results demonstrate the existence of segregated parieto-premotor-motor pathways crucial for preparation of different grasping actions and indicate that these may process information relevant to both the position of the object and the hand shape required to use it., (Copyright (c) 2010 Elsevier Inc. All rights reserved.)