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      Functional ultrasound imaging of intrinsic connectivity in the living rat brain with high spatiotemporal resolution

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          Abstract

          Long-range coherences in spontaneous brain activity reflect functional connectivity. Here we propose a novel, highly resolved connectivity mapping approach, using ultrafast functional ultrasound (fUS), which enables imaging of cerebral microvascular haemodynamics deep in the anaesthetized rodent brain, through a large thinned-skull cranial window, with pixel dimensions of 100 μm × 100 μm in-plane. The millisecond-range temporal resolution allows unambiguous cancellation of low-frequency cardio-respiratory noise. Both seed-based and singular value decomposition analysis of spatial coherences in the low-frequency (<0.1 Hz) spontaneous fUS signal fluctuations reproducibly report, at different coronal planes, overlapping high-contrast, intrinsic functional connectivity patterns. These patterns are similar to major functional networks described in humans by resting-state fMRI, such as the lateral task-dependent network putatively anticorrelated with the midline default-mode network. These results introduce fUS as a powerful novel neuroimaging method, which could be extended to portable systems for three-dimensional functional connectivity imaging in awake and freely moving rodents.

          Abstract

          Functional connectivity of brain networks is poorly understood, in part, due to limited imaging approaches. Here, the authors use ultrasound imaging to study functional connectivity in the adult rat brain in vivo, allowing for the identification of highly contrasted intrinsic connectivity patterns.

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          Most cited references49

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          Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI.

          Subtle changes in a subject's breathing rate or depth, which occur naturally during rest at low frequencies (<0.1 Hz), have been shown to be significantly correlated with fMRI signal changes throughout gray matter and near large vessels. The goal of this study was to investigate the impact of these low-frequency respiration variations on both task activation fMRI studies and resting-state functional connectivity analysis. Unlike MR signal changes correlated with the breathing motion ( approximately 0.3 Hz), BOLD signal changes correlated with across-breath variations in respiratory volume ( approximately 0.03 Hz) appear localized to blood vessels and regions with high blood volume, such as gray matter, similar to changes seen in response to a breath-hold challenge. In addition, the respiration-variation-induced signal changes were found to coincide with many of the areas identified as part of the 'default mode' network, a set of brain regions hypothesized to be more active at rest. Regions could therefore be classified as being part of a resting network based on their similar respiration-induced changes rather than their synchronized neuronal activity. Monitoring and removing these respiration variations led to a significant improvement in the identification of task-related activation and deactivation and only slight differences in regions correlated with the posterior cingulate at rest. Regressing out global signal changes or cueing the subject to breathe at a constant rate and depth resulted in an improved spatial overlap between deactivations and resting-state correlations among areas that showed deactivation.
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            Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate.

            Transcranial magnetic stimulation (TMS) to the left dorsolateral prefrontal cortex (DLPFC) is used clinically for the treatment of depression. However, the antidepressant mechanism remains unknown and its therapeutic efficacy remains limited. Recent data suggest that some left DLPFC targets are more effective than others; however, the reasons for this heterogeneity and how to capitalize on this information remain unclear. Intrinsic (resting state) functional magnetic resonance imaging data from 98 normal subjects were used to compute functional connectivity with various left DLPFC TMS targets employed in the literature. Differences in functional connectivity related to differences in previously reported clinical efficacy were identified. This information was translated into a connectivity-based targeting strategy to identify optimized left DLPFC TMS coordinates. Results in normal subjects were tested for reproducibility in an independent cohort of 13 patients with depression. Differences in functional connectivity were related to previously reported differences in clinical efficacy across a distributed set of cortical and limbic regions. Dorsolateral prefrontal cortex TMS sites with better clinical efficacy were more negatively correlated (anticorrelated) with the subgenual cingulate. Optimum connectivity-based stimulation coordinates were identified in Brodmann area 46. Results were reproducible in patients with depression. Reported antidepressant efficacy of different left DLPFC TMS sites is related to the anticorrelation of each site with the subgenual cingulate, potentially lending insight into the antidepressant mechanism of TMS and suggesting a role for intrinsically anticorrelated networks in depression. These results can be translated into a connectivity-based targeting strategy for focal brain stimulation that might be used to optimize clinical response. Copyright © 2012 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
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              Resting-state functional connectivity in neuropsychiatric disorders.

              This review considers recent advances in the application of resting-state functional magnetic resonance imaging to the study of neuropsychiatric disorders. Resting-state functional magnetic resonance imaging is a relatively novel technique that has several potential advantages over task-activation functional magnetic resonance imaging in terms of its clinical applicability. A number of research groups have begun to investigate the use of resting-state functional magnetic resonance imaging in a variety of neuropsychiatric disorders including Alzheimer's disease, depression, and schizophrenia. Although preliminary results have been fairly consistent in some disorders (for example, Alzheimer's disease) they have been less reproducible in others (schizophrenia). Resting-state connectivity has been shown to correlate with behavioral performance and emotional measures. It's potential as a biomarker of disease and an early objective marker of treatment response is genuine but still to be realized. Resting-state functional magnetic resonance imaging has made some strides in the clinical realm but significant advances are required before it can be used in a meaningful way at the single-patient level.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Pub. Group
                2041-1723
                03 October 2014
                : 5
                : 5023
                Affiliations
                [1 ]Institut Langevin, ESPCI-ParisTech , 1 rue Cuvier, 75005 Paris, France
                [2 ]CNRS UMR 7587 , 1 rue Cuvier, 75005 Paris, France
                [3 ]INSERM U979 ‘Wave Physics for Medicine’ Lab , 1 rue Cuvier, 75005 Paris, France
                [4 ]Centre National pour la Recherche Scientifique, UMR 8249 , 10 rue Vauquelin, 75005 Paris, France
                [5 ]Brain Plasticity Unit, ESPCI-ParisTech , 10 rue Vauquelin, 75005 Paris, France
                Author notes
                [*]

                These authors contributed equally to this work

                [†]

                These authors jointly supervised this work

                Article
                ncomms6023
                10.1038/ncomms6023
                4205893
                25277668
                9bdcd293-2a9a-4721-97cd-2f7066479181
                Copyright © 2014, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 06 April 2014
                : 20 August 2014
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