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      Default Mode Network Structural Integrity and Cerebellar Connectivity Predict Information Processing Speed Deficit in Multiple Sclerosis

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          Abstract

          Cognitive impairment affects about 50% of multiple sclerosis (MS) patients, but the mechanisms underlying this remain unclear. The default mode network (DMN) has been linked with cognition, but in MS its role is still poorly understood. Moreover, within an extended DMN network including the cerebellum (CBL-DMN), the contribution of cortico-cerebellar connectivity to MS cognitive performance remains unexplored. The present study investigated associations of DMN and CBL-DMN structural connectivity with cognitive processing speed in MS, in both cognitively impaired (CIMS) and cognitively preserved (CPMS) MS patients. 68 MS patients and 22 healthy controls (HCs) completed a symbol digit modalities test (SDMT) and had 3T brain magnetic resonance imaging (MRI) scans that included a diffusion weighted imaging protocol. DMN and CBL-DMN tracts were reconstructed with probabilistic tractography. These networks (DMN and CBL-DMN) and the cortico-cerebellar tracts alone were modeled using a graph theoretical approach with fractional anisotropy (FA) as the weighting factor. Brain parenchymal fraction (BPF) was also calculated. In CIMS SDMT scores strongly correlated with the FA-weighted global efficiency (GE) of the network [GE(CBL-DMN): ρ = 0.87, R 2 = 0.76, p < 0.001; GE(DMN): ρ = 0.82, R 2 = 0.67, p < 0.001; GE(CBL): ρ = 0.80, R 2 = 0.64, p < 0.001]. In CPMS the correlation between these measures was significantly lower [GE(CBL-DMN): ρ = 0.51, R 2 = 0.26, p < 0.001; GE(DMN): ρ = 0.48, R 2 = 0.23, p = 0.001; GE(CBL): ρ = 0.52, R 2 = 0.27, p < 0.001] and SDMT scores correlated most with BPF (ρ = 0.57, R 2 = 0.33, p < 0.001). In a multivariable regression model where SDMT was the independent variable, FA-weighted GE was the only significant explanatory variable in CIMS, while in CPMS BPF and expanded disability status scale were significant. No significant correlation was found in HC between SDMT scores, MRI or network measures. DMN structural GE is related to cognitive performance in MS, and results of CBL-DMN suggest that the cerebellum structural connectivity to the DMN plays an important role in information processing speed decline.

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          Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution.

          Diffusion-weighted (DW) MR images contain information about the orientation of brain white matter fibres that potentially can be used to study human brain connectivity in vivo using tractography techniques. Currently, the diffusion tensor model is widely used to extract fibre directions from DW-MRI data, but fails in regions containing multiple fibre orientations. The spherical deconvolution technique has recently been proposed to address this limitation. It provides an estimate of the fibre orientation distribution (FOD) by assuming the DW signal measured from any fibre bundle is adequately described by a single response function. However, the deconvolution is ill-conditioned and susceptible to noise contamination. This tends to introduce artefactual negative regions in the FOD, which are clearly physically impossible. In this study, the introduction of a constraint on such negative regions is proposed to improve the conditioning of the spherical deconvolution. This approach is shown to provide FOD estimates that are robust to noise whilst preserving angular resolution. The approach also permits the use of super-resolution, whereby more FOD parameters are estimated than were actually measured, improving the angular resolution of the results. The method provides much better defined fibre orientation estimates, and allows orientations to be resolved that are separated by smaller angles than previously possible. This should allow tractography algorithms to be designed that are able to track reliably through crossing fibre regions.
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            MRtrix: Diffusion tractography in crossing fiber regions

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              Evidence for topographic organization in the cerebellum of motor control versus cognitive and affective processing.

              Patients with cerebellar damage often present with the cerebellar motor syndrome of dysmetria, dysarthria and ataxia, yet cerebellar lesions can also result in the cerebellar cognitive affective syndrome (CCAS), including executive, visual spatial, and linguistic impairments, and affective dysregulation. We have hypothesized that there is topographic organization in the human cerebellum such that the anterior lobe and lobule VIII contain the representation of the sensorimotor cerebellum; lobules VI and VII of the posterior lobe comprise the cognitive cerebellum; and the posterior vermis is the anatomical substrate of the limbic cerebellum. Here we analyze anatomical, functional neuroimaging, and clinical data to test this hypothesis. We find converging lines of evidence supporting regional organization of motor, cognitive, and limbic behaviors in the cerebellum. The cerebellar motor syndrome results when lesions involve the anterior lobe and parts of lobule VI, interrupting cerebellar communication with cerebral and spinal motor systems. Cognitive impairments occur when posterior lobe lesions affect lobules VI and VII (including Crus I, Crus II, and lobule VIIB), disrupting cerebellar modulation of cognitive loops with cerebral association cortices. Neuropsychiatric disorders manifest when vermis lesions deprive cerebro-cerebellar-limbic loops of cerebellar input. We consider this functional topography to be a consequence of the differential arrangement of connections of the cerebellum with the spinal cord, brainstem, and cerebral hemispheres, reflecting cerebellar incorporation into the distributed neural circuits subserving movement, cognition, and emotion. These observations provide testable hypotheses for future investigations. Copyright (c) 2009 Elsevier Srl. All rights reserved.
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                Author and article information

                Contributors
                Journal
                Front Cell Neurosci
                Front Cell Neurosci
                Front. Cell. Neurosci.
                Frontiers in Cellular Neuroscience
                Frontiers Media S.A.
                1662-5102
                11 February 2019
                2019
                : 13
                : 21
                Affiliations
                [1] 1Department of Physics, University of Milan , Milan, Italy
                [2] 2Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa , Genoa, Italy
                [3] 3Ospedale Policlinico S. Martino , Genoa, Italy
                [4] 4Department of Electrical, Computer and Biomedical Engineering, University of Pavia , Pavia, Italy
                [5] 5NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, Institute of Neurology, University College London , London, United Kingdom
                [6] 6National Institute for Health Research, University College London Hospitals, Biomedical Research Centre , London, United Kingdom
                [7] 7Department of Brain and Behavioral Sciences, University of Pavia , Pavia, Italy
                [8] 8Brain Connectivity Center, IRCCS Mondino Foundation , Pavia, Italy
                [9] 9Brain MRI 3T Mondino Research Center, IRCCS Mondino Foundation , Pavia, Italy
                Author notes

                Edited by: Federico Giove, Centro Fermi – Museo Storico della Fisica e Centro Studi e Ricerche Enrico Fermi, Italy

                Reviewed by: Tommaso Gili, IMT School for Advanced Studies Lucca, Italy; Patrizia Pantano, Sapienza University of Rome, Italy

                *Correspondence: Giovanni Savini, giovanni.savini@ 123456unimi.it
                Article
                10.3389/fncel.2019.00021
                6396736
                30853896
                6ccf434a-5ad0-42ee-b6bf-4681b38833c0
                Copyright © 2019 Savini, Pardini, Castellazzi, Lascialfari, Chard, D’Angelo and Gandini Wheeler-Kingshott.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 02 July 2018
                : 17 January 2019
                Page count
                Figures: 7, Tables: 4, Equations: 0, References: 86, Pages: 15, Words: 0
                Categories
                Neuroscience
                Original Research

                Neurosciences
                default mode network (dmn),cerebellum,multiple sclerosis (ms),symbol digit modalities test (sdmt),connectomics,tractography,diffusion weighted imaging (dwi),magnetic resonance imaging (mri)

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