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      Altered regional activity and inter-regional functional connectivity in psychogenic non-epileptic seizures

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          Abstract

          Although various imaging studies have focused on detecting the cerebral function underlying psychogenic non-epileptic seizures (PNES), the nature of PNES remains poorly understood. In this study, we combined the resting state fMRI with fractional amplitude of low-frequency fluctuations (fALFF) and functional connectivity based on the seed voxel linear correlation approach to examine the alterations of regional and inter-regional network cerebral functions in PNES. A total of 20 healthy controls and 18 patients were enrolled. The PNES patients showed significantly increased fALFF mainly in the dorsolateral prefrontal cortex (DLPFC), parietal cortices, and motor areas, as well as decreased fALFF in the triangular inferior frontal gyrus. Thus, our results add to literature suggesting abnormalities of neural synchrony in PNES. Moreover, PNES exhibited widespread inter-regional neural network deficits, including increased (DLPFC, sensorimotor, and limbic system) and decreased (ventrolateral prefrontal cortex) connectivity, indicating that changes in the regional cerebral function are related to remote inter-regional network deficits. Correlation analysis results revealed that the connectivity between supplementary motor area and anterior cingulate cortex correlated with the PNES frequency, further suggesting the skewed integration of synchronous activity could predispose to the occurrence of PNES. Our findings provided novel evidence to investigate the pathophysiological mechanisms of PNES.

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          Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI.

          In children with attention deficit hyperactivity disorder (ADHD), functional neuroimaging studies have revealed abnormalities in various brain regions, including prefrontal-striatal circuit, cerebellum, and brainstem. In the current study, we used a new marker of functional magnetic resonance imaging (fMRI), amplitude of low-frequency (0.01-0.08Hz) fluctuation (ALFF) to investigate the baseline brain function of this disorder. Thirteen boys with ADHD (13.0+/-1.4 years) were examined by resting-state fMRI and compared with age-matched controls. As a result, we found that patients with ADHD had decreased ALFF in the right inferior frontal cortex, [corrected] and bilateral cerebellum and the vermis as well as increased ALFF in the right anterior cingulated cortex, left sensorimotor cortex, and bilateral brainstem. This resting-state fMRI study suggests that the changed spontaneous neuronal activity of these regions may be implicated in the underlying pathophysiology in children with ADHD.
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            Left ventrolateral prefrontal cortex and the cognitive control of memory.

            Cognitive control mechanisms permit memory to be accessed strategically, and so aid in bringing knowledge to mind that is relevant to current goals and actions. In this review, we consider the contribution of left ventrolateral prefrontal cortex (VLPFC) to the cognitive control of memory. Reviewed evidence supports a two-process model of mnemonic control, supported by a double dissociation among rostral regions of left VLPFC. Specifically, anterior VLPFC (approximately BA 47; inferior frontal gyrus pars orbitalis) supports controlled access to stored conceptual representations, whereas mid-VLPFC (approximately BA 45; inferior frontal gyrus pars triangularis) supports a domain-general selection process that operates post-retrieval to resolve competition among active representations. We discuss the contribution of these control mechanisms across a range of mnemonic domains, including semantic retrieval, recollection of contextual details about past events, resolution of proactive interference in working memory, and task switching. Finally, we consider open directions for future research into left VLPFC function and the cognitive control of memory.
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              Correlations and anticorrelations in resting-state functional connectivity MRI: a quantitative comparison of preprocessing strategies.

              Resting-state data sets contain coherent fluctuations unrelated to neural processes originating from residual motion artefacts, respiration and cardiac action. Such confounding effects may introduce correlations and cause an overestimation of functional connectivity strengths. In this study we applied several multidimensional linear regression approaches to remove artificial coherencies and examined the impact of preprocessing on sensitivity and specificity of functional connectivity results in simulated data and resting-state data sets from 40 subjects. Furthermore, we aimed at clarifying possible causes of anticorrelations and test the hypothesis that anticorrelations are introduced via certain preprocessing approaches, with particular focus on the effects of regression against the global signal. Our results show that preprocessing in general greatly increased connection specificity, in particular correction for global signal fluctuations almost doubled connection specificity. However, widespread anticorrelated networks were only found when regression against the global signal was applied. Results in simulated data sets compared with result of human data strongly suggest that anticorrelations are indeed introduced by global signal regression and should therefore be interpreted very carefully. In addition, global signal regression may also reduce the sensitivity for detecting true correlations, i.e. increase the number of false negatives. Concluding from our results we suggest that is highly recommended to apply correction against realignment parameters, white matter and ventricular time courses, as well as the global signal to maximize the specificity of positive resting-state correlations.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                25 June 2015
                2015
                : 5
                : 11635
                Affiliations
                [1 ]Key Laboratory for Neuroinformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China , Chengdu 610041, PR China
                [2 ]Department of Neurology, West China Hospital of Sichuan University , Chengdu 610041, PR China
                [3 ]Department of Radiology, West China Hospital of Sichuan University , Chengdu 610041, PR China
                Author notes
                Article
                srep11635
                10.1038/srep11635
                4480007
                26109123
                0ade65df-f556-4d6b-8087-0ff549bbd654
                Copyright © 2015, Macmillan Publishers Limited

                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
                : 11 February 2015
                : 01 June 2015
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