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The brain has a unique macroscopic waste clearance system, termed the glymphatic system which utilises perivascular tunnels surrounded by astroglia to promote cerebrospinal-interstitial fluid exchange. Rodent studies have demonstrated a marked increase in glymphatic clearance during sleep which has been linked to a sleep-induced expansion of the extracellular space and concomitant reduction in intracellular volume. However, despite being implicated in the pathophysiology of multiple human neurodegenerative disorders, non-invasive techniques for imaging glymphatic clearance in humans are currently limited. Here we acquired multi-shell diffusion weighted MRI (dwMRI) in twenty-one healthy young participants (6 female, 22.3 ± 3.2 years) each scanned twice, once during wakefulness and once during sleep induced by a combination of one night of sleep deprivation and 10 mg of the hypnotic zolpidem 30 min before scanning. To capture hypothesised sleep-associated changes in intra/extracellular space, dwMRI were analysed using higher order diffusion modelling with the prediction that sleep-associated increases in interstitial (extracellular) fluid volume would result in a decrease in diffusion kurtosis, particularly in areas associated with slow wave generation at the onset of sleep. In line with our hypothesis, we observed a global reduction in diffusion kurtosis (t 15 =2.82, p = 0.006) during sleep as well as regional reductions in brain areas associated with slow wave generation during early sleep and default mode network areas that are highly metabolically active during wakefulness. Analysis with a higher-order representation of diffusion (MAP-MRI) further indicated that changes within the intra/extracellular domain rather than membrane permeability likely underpin the observed sleep-associated decrease in kurtosis. These findings identify higher-order modelling of dwMRI as a potential new non-invasive method for imaging glymphatic clearance and extend rodent findings to suggest that sleep is also associated with an increase in interstitial fluid volume in humans., Competing Interests: Declaration of Competing Interests None., (Copyright © 2023. Published by Elsevier Inc.)

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.)

The MRI signal is dependent upon a number of sub-voxel properties of tissue, which makes it potentially able to detect changes occurring at a scale much smaller than the image resolution. This "microstructural imaging" has become one of the main branches of quantitative MRI. Despite the exciting promise of unique insight beyond the resolution of the acquired images, its widespread application is limited by the relatively modest ability of each microstructural imaging technique to distinguish between differing microscopic substrates. This is mainly due to the fact that MRI provides a very indirect measure of the tissue properties in which we are interested. A strategy to overcome this limitation lies in the combination of more than one technique, to exploit the relative contributions of differing physiological and pathological substrates to selected MRI contrasts. This forms the basis of multi-modal MRI, a broad concept that refers to many different ways of effectively combining information from more than one MRI contrast. This paper will review a range of methods that have been proposed to maximise the output of this combination, primarily falling into one of two approaches. The first one relies on data-driven methods, exploiting multivariate analysis tools able to capture overlapping and complementary information. The second approach, which we call "model-driven", aims at combining parameters extracted by existing biophysical or signal models to obtain new parameters, which are believed to be more accurate or more specific than the original ones. This paper will attempt to provide an overview of the advantages and limitations of these two philosophies., (Copyright © 2017 The Author(s). Published by 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.)

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.)

Background: Loss of brain volume in first-episode psychosis can be detected using conventional magnetic resonance imaging (MRI), but subtle changes--not leading to reduction in volume--that may contribute to clinical and cognitive abnormalities, may go undetected. Magnetization transfer imaging (MTI), a technique more sensitive to subtle neuropathological changes than conventional MRI, could yield important information on the extent and nature of structural abnormalities., Methods: Forty-eight patients (33 males) from a population-based sample with first-episode psychosis (41 with schizophrenia and 7 with schizoaffective psychosis) and 47 healthy volunteers (27 males) were studied. Differences in magnetization transfer ratio (MTR) and white and grey matter volumes between groups were investigated., Results: In patients, MTR was reduced in right entorhinal cortex, fusiform, dentate and superior frontal gyri and in left superior frontal and inferior/rostral cingulate gyri. Grey matter volume was reduced in right insula, frontal operculum and middle and superior temporal gyri and in left middle temporal gyrus. Grey matter volume increases were seen in patients in the superior frontal gyrus. White matter volume loss was found adjacent to grey matter loss. In patients MTR was lower in all areas of volumetric differences between groups suggesting that both changes may be related. Similar findings were observed when patients with schizoaffective psychosis were removed from the analysis. The correlations between clinical and MRI parameters did not survive correction for multiple comparisons., Conclusions: MTI frontal and temporal abnormalities suggesting neuroaxonal and myelin changes were more extensive in our patients than those detected with conventional MRI. Our findings also suggest that there is regional variation in the severity of structural brain abnormalities.

A model of disconnectivity involving abnormalities in the cortex and connecting white matter pathways may explain the symptoms and cognitive abnormalities of schizophrenia. Recently, diffusion imaging tractography has made it possible to study white matter pathways in detail, and we present here a study of patients with first-episode psychosis using this technique. We studied the uncinate fasciculus (UF), the largest white matter tract that connects the frontal and temporal lobes, two brain regions significantly implicated in schizophrenia. Nineteen patients with first-episode schizophrenia and 23 controls were studied using a probabilistic tractography algorithm (PICo). Fractional anisotropy (FA) and probability of connection were obtained for every voxel in the tract, and the group means and distributions of these variables were compared. The spread of the FA distribution in the upper tail, as measured by the squared coefficient of variance (SCV), was reduced in the left UF in the patient group, indicating that the number of voxels with high FA values was reduced in the core of the tract and suggesting the presence of changes in fibre alignment and tract coherence in the patient group. The SCV of FA was lower in females across both groups and there was no correlation between the SCV of FA and clinical ratings.

A model of disconnectivity involving abnormalities in the cortex and connecting white matter pathways may explain the clinical manifestations of schizophrenia. Recently, diffusion imaging tractography has made it possible to study white matter pathways in detail and we present here a study of patients with first-episode psychosis using this technique. We selected the corpus callosum for this study because there is evidence that it is abnormal in schizophrenia. In addition, the topographical organization of its fibers makes it possible to relate focal abnormalities to specific cortical regions. Eighteen patients with first-episode psychosis and 21 healthy subjects took part in the study. A probabilistic tractography algorithm (PICo) was used to study fractional anisotropy (FA). Seed regions were placed in the genu and splenium to track fiber tracts traversing these regions, and a multi-threshold approach to study the probability of connection was used. Multiple linear regressions were used to explore group differences. FA, a measure of tract coherence, was reduced in tracts crossing the genu, and to a lesser degree the splenium, in patients compared with controls. FA was also lower in the genu in females across both groups, but there was no gender-by-group interaction. The FA reduction in patients may be due to aberrant myelination or axonal abnormalities, but the similar tract volumes in the two groups suggest that severe axonal loss is unlikely at this stage of the illness.

This study investigates some of the issues involved in magnetization transfer ratio (MTR) acquisition, and in particular aims to determine whether high quality in vivo MTR measurements can be made at 3.0 T. The dependency of the MTR white-to-grey matter contrast to noise ratio (CNR) on MT pulse characteristics at 1.5 T and at 3.0 T was investigated using an established two-pool model for MT. The simulations showed that MT pulse parameters optimizing the CNR can be derived for both field strengths. Both the SNR and the CNR of MTR maps at 3.0 T were increased compared to 1.5 T. Images obtained using a safe in vivo MTR acquisition protocol based on results of simulations at 3.0 T are presented.

Quantitative magnetisation transfer (MT) analysis is based on a two-pool model of magnetisation transfer and allows important physical properties of the two proton pools to be assessed. A good signal-to-noise ratio (SNR) for the measured signal is essential in order to estimate reliably the parameters from a small number of samples, thus prompting the use of a sequence with high SNR, such as a three-dimensional spoiled gradient acquisition. Here, we show how full brain coverage can be accomplished efficiently, using a three-dimensional acquisition, in a clinically acceptable time, and without the use of large numbers of slice-selective radio-frequency pulses which could otherwise confound analysis. This acquisition was first compared in post mortem human brain tissue to established two-dimensional acquisition protocols with differing SNR levels and then used to collect data from six healthy subjects. Image data were fitted using the two pool model and showed negligible residual deviations. Quantitative results were assessed in several brain locations. Results were consistent with previous single-slice data, and parametric maps were of good quality. Further investigations are needed to interpret the regional variation of quantitative MT quantities.