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      Insular and occipital changes in visual snow syndrome: a BOLD fMRI and MRS study

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          Abstract

          Objective

          To investigate the pathophysiology of visual snow (VS), through a combined functional neuroimaging and magnetic resonance spectroscopy ( 1H‐MRS) approach.

          Methods

          We applied a functional MRI block‐design protocol studying the responses to a visual stimulation mimicking VS, in combination with 1H‐MRS over the right lingual gyrus, in 24 patients with VS compared to an equal number of age‐ and gender‐matched healthy controls.

          Results

          We found reduced BOLD responses to the visual stimulus with respect to baseline in VS patients compared to controls, in the left ( k = 291; P = 0.025; peak MNI coordinate [‐34 12 ‐6]) and right ( k = 100; P = 0.003; peak MNI coordinate [44 14 ‐2]) anterior insula. Our spectroscopy analysis revealed a significant increase in lactate concentrations in patients with respect to controls (0.66 ± 0.9 mmol/L vs. 0.07 ± 0.2 mmol/L; P < 0.001) in the right lingual gyrus. In this area, there was a significant negative correlation between lactate concentrations and BOLD responses to visual stimulation ( P = 0.004; r = −0.42), which was dependent on belonging to the patient group.

          Interpretation

          As shown by our BOLD analysis, VS is characterized by a difference in bilateral insular responses to a visual stimulus mimicking VS itself, which could be due to disruptions within the salience network. Our results also suggest that patients with VS have a localized disturbance in extrastriate anaerobic metabolism, which may in turn cause a decreased metabolic reserve for the regular processing of visual stimuli.

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          Most cited references32

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          Brain energy metabolism: focus on astrocyte-neuron metabolic cooperation.

          The energy requirements of the brain are very high, and tight regulatory mechanisms operate to ensure adequate spatial and temporal delivery of energy substrates in register with neuronal activity. Astrocytes-a type of glial cell-have emerged as active players in brain energy delivery, production, utilization, and storage. Our understanding of neuroenergetics is rapidly evolving from a "neurocentric" view to a more integrated picture involving an intense cooperativity between astrocytes and neurons. This review focuses on the cellular aspects of brain energy metabolism, with a particular emphasis on the metabolic interactions between neurons and astrocytes. Copyright © 2011 Elsevier Inc. All rights reserved.
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            A unified statistical approach for determining significant signals in images of cerebral activation.

            We present a unified statistical theory for assessing the significance of apparent signal observed in noisy difference images. The results are usable in a wide range of applications, including fMRI, but are discussed with particular reference to PET images which represent changes in cerebral blood flow elicited by a specific cognitive or sensorimotor task. Our main result is an estimate of the P-value for local maxima of Gaussian, t, chi(2) and F fields over search regions of any shape or size in any number of dimensions. This unifies the P-values for large search areas in 2-D (Friston et al. [1991]: J Cereb Blood Flow Metab 11:690-699) large search regions in 3-D (Worsley et al. [1992]: J Cereb Blood Flow Metab 12:900-918) and the usual uncorrected P-value at a single pixel or voxel. Copyright (c) 1996 Wiley-Liss, Inc.
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              Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses.

              The aim of group fMRI studies is to relate contrasts of tasks or stimuli to regional brain activity increases. These studies typically involve 10 to 16 subjects. The average regional activity statistical significance is assessed using the subject to subject variability of the effect (random effects analyses). Because of the relatively small number of subjects included, the sensitivity and reliability of these analyses is questionable and hard to investigate. In this work, we use a very large number of subject (more than 80) to investigate this issue. We take advantage of this large cohort to study the statistical properties of the inter-subject activity and focus on the notion of reproducibility by bootstrapping. We asked simple but important methodological questions: Is there, from the point of view of reliability, an optimal statistical threshold for activity maps? How many subjects should be included in group studies? What method should be preferred for inference? Our results suggest that i) optimal thresholds can indeed be found, and are rather lower than usual corrected for multiple comparison thresholds, ii) 20 subjects or more should be included in functional neuroimaging studies in order to have sufficient reliability, iii) non-parametric significance assessment should be preferred to parametric methods, iv) cluster-level thresholding is more reliable than voxel-based thresholding, and v) mixed effects tests are much more reliable than random effects tests. Moreover, our study shows that inter-subject variability plays a prominent role in the relatively low sensitivity and reliability of group studies.
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                Author and article information

                Contributors
                francesca.puledda@kcl.ac.uk
                Journal
                Ann Clin Transl Neurol
                Ann Clin Transl Neurol
                10.1002/(ISSN)2328-9503
                ACN3
                Annals of Clinical and Translational Neurology
                John Wiley and Sons Inc. (Hoboken )
                2328-9503
                10 March 2020
                March 2020
                : 7
                : 3 ( doiID: 10.1002/acn3.v7.3 )
                : 296-306
                Affiliations
                [ 1 ] Headache Group Department of Basic and Clinical Neuroscience Institute of Psychiatry, Psychology & Neuroscience King’s College London London United Kingdom
                [ 2 ] NIHR‐Wellcome Trust King’s Clinical Research Facility King’s College Hospital London United Kingdom
                [ 3 ] Department of Old Age Psychiatry Institute of Psychiatry, Psychology & Neuroscience King’s College London London United Kingdom
                [ 4 ] Centre for Neuroimaging Sciences Department of Neuroimaging Institute of Psychiatry, Psychology & Neuroscience King’s College London London United Kingdom
                [ 5 ] Department of Neurology, Inselspital Bern University Hospital University of Bern Bern Switzerland
                Author notes
                [*] [* ] Correspondence

                Francesca Puledda, King’s College London, London SE5 9PJ, United Kingdom.

                Email: francesca.puledda@ 123456kcl.ac.uk

                Author information
                https://orcid.org/0000-0002-1933-4049
                https://orcid.org/0000-0002-4214-9642
                https://orcid.org/0000-0002-5078-9025
                https://orcid.org/0000-0003-3260-5904
                Article
                ACN350986
                10.1002/acn3.50986
                7086005
                32154676
                a896a467-c205-4826-8253-053711d5908e
                © 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 08 December 2019
                : 13 January 2020
                Page count
                Figures: 5, Tables: 2, Pages: 11, Words: 6963
                Funding
                Funded by: National Institute for Health Research , open-funder-registry 10.13039/501100000272;
                This work was funded by National Institute for Health Research , open-funder-registry 10.13039/501100000272; grant .
                Categories
                Research Article
                Research Articles
                Custom metadata
                2.0
                March 2020
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.8 mode:remove_FC converted:22.03.2020

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