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      Presurgical thalamocortical connectivity is associated with response to vagus nerve stimulation in children with intractable epilepsy

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          Abstract

          Although chronic vagus nerve stimulation (VNS) is an established treatment for medically-intractable childhood epilepsy, there is considerable heterogeneity in seizure response and little data are available to pre-operatively identify patients who may benefit from treatment. Since the therapeutic effect of VNS may be mediated by afferent projections to the thalamus, we tested the hypothesis that intrinsic thalamocortical connectivity is associated with seizure response following chronic VNS in children with epilepsy. Twenty-one children (ages 5–21 years) with medically-intractable epilepsy underwent resting-state fMRI prior to implantation of VNS. Ten received sedation, while 11 did not. Whole brain connectivity to thalamic regions of interest was performed. Multivariate generalized linear models were used to correlate resting-state data with seizure outcomes, while adjusting for age and sedation status. A supervised support vector machine (SVM) algorithm was used to classify response to chronic VNS on the basis of intrinsic connectivity. Of the 21 subjects, 11 (52%) had 50% or greater improvement in seizure control after VNS. Enhanced connectivity of the thalami to the anterior cingulate cortex (ACC) and left insula was associated with greater VNS efficacy. Within our test cohort, SVM correctly classified response to chronic VNS with 86% accuracy. In an external cohort of 8 children, the predictive model correctly classified the seizure response with 88% accuracy. We find that enhanced intrinsic connectivity within thalamocortical circuitry is associated with seizure response following VNS. These results encourage the study of intrinsic connectivity to inform neural network-based, personalized treatment decisions for children with intractable epilepsy.

          Highlights

          • Children demonstrate variable response to vagus nerve stimulation (VNS).

          • Enhanced thalamocortical connectivity is associated with better response to VNS.

          • Functional connectivity may pre-operatively identify responders to VNS.

          • Further study is indicated to inform personalized treatment decisions.

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          Most cited references34

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          Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers.

          Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically meaningful differentiations. Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations.
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            Visual inspection of independent components: defining a procedure for artifact removal from fMRI data.

            Artifacts in functional magnetic resonance imaging (fMRI) data, primarily those related to motion and physiological sources, negatively impact the functional signal-to-noise ratio in fMRI studies, even after conventional fMRI preprocessing. Independent component analysis' demonstrated capacity to separate sources of neural signal, structured noise, and random noise into separate components might be utilized in improved procedures to remove artifacts from fMRI data. Such procedures require a method for labeling independent components (ICs) as representing artifacts to be removed or neural signals of interest to be spared. Visual inspection is often considered an accurate method for such labeling as well as a standard to which automated labeling methods are compared. However, detailed descriptions of methods for visual inspection of ICs are lacking in the literature. Here we describe the details of, and the rationale for, an operationalized fMRI data denoising procedure that involves visual inspection of ICs (96% inter-rater agreement). We estimate that dozens of subjects/sessions can be processed within a few hours using the described method of visual inspection. Our hope is that continued scientific discussion of and testing of visual inspection methods will lead to the development of improved, cost-effective fMRI denoising procedures. Copyright (c) 2010 Elsevier B.V. All rights reserved.
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              A multicenter pilot study of subcallosal cingulate area deep brain stimulation for treatment-resistant depression.

              Deep brain stimulation (DBS) has been recently investigated as a treatment for major depression. One of the proposed targets for this application is the subcallosal cingulate gyrus (SCG). To date, promising results after SCG DBS have been reported by a single center. In the present study the authors investigated whether these findings may be replicated at different institutions. They conducted a 3-center prospective open-label trial of SCG DBS for 12 months in patients with treatment-resistant depression. Twenty-one patients underwent implantation of bilateral SCG electrodes. The authors examined the reduction in Hamilton Rating Scale for Depression (HRSD-17) score from baseline (RESP50). Patients treated with SCG DBS had an RESP50 of 57% at 1 month, 48% at 6 months, and 29% at 12 months. The response rate after 12 months of DBS, however, increased to 62% when defined as a reduction in the baseline HRSD-17 of 40% or more. Reductions in depressive symptomatology were associated with amelioration in disease severity in patients who responded to surgery. Overall, findings from this study corroborate the results of previous reports showing that outcome of SCG DBS may be replicated across centers.
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                Author and article information

                Contributors
                Journal
                Neuroimage Clin
                Neuroimage Clin
                NeuroImage : Clinical
                Elsevier
                2213-1582
                22 September 2017
                2017
                22 September 2017
                : 16
                : 634-642
                Affiliations
                [a ]Division of Neurosurgery, Brain Institute, Nicklaus Children's Hospital, Miami, FL, USA
                [b ]Division of Neurosurgery, University of Miami/Miller School of Medicine, Miami, FL, USA
                [c ]Division of Neurosurgery, Department of Surgery, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
                [d ]Department of Neurology, Brain Institute, Nicklaus Children's Hospital, Miami, FL, USA
                [e ]Department of Radiology, Nicklaus Children's Hospital, Miami, FL, USA
                [f ]Faculty of Medicine, University of Toronto, Toronto, ON, Canada
                [g ]Division of Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada
                [h ]Department of Neurosurgery, Mattel Children's Hospital, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, California, USA
                [i ]Division of Neurosurgery, CHU Sainte-Justine Hospital, University of Montreal, Montreal, QC, Canada
                Author notes
                [* ]Corresponding author at: Division of Neurosurgery, Hospital for Sick Children, Department of Surgery, University of Toronto, 1503 – 555 University Ave, Toronto, ON M5G 2R2, Canada.Division of NeurosurgeryHospital for Sick ChildrenDepartment of SurgeryUniversity of Toronto1503 – 555 University AveTorontoONM5G 2R2Canada george.ibrahim@ 123456sickkids.ca
                Article
                S2213-1582(17)30229-2
                10.1016/j.nicl.2017.09.015
                5619991
                28971013
                09c53947-f4b9-484a-9198-2fe9f6004e79
                © 2017 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 17 July 2017
                : 16 September 2017
                : 21 September 2017
                Categories
                Regular Article

                functional connectivity,intrinsic connectivity networks,resting-state fmri,low frequency neural oscillations,vns

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