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      Modafinil Alters Intrinsic Functional Connectivity of the Right Posterior Insula: A Pharmacological Resting State fMRI Study

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      1 , 1 , 1 , 2 , 3 , *
      PLoS ONE
      Public Library of Science

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          Abstract

          Background

          Modafinil is employed for the treatment of narcolepsy and has also been, off-label, used to treat cognitive dysfunction in neuropsychiatric disorders. In a previous study, we have reported that single dose administration of modafinil in healthy young subjects enhances fluid reasoning and affects resting state activity in the Fronto Parietal Control (FPC) and Dorsal Attention (DAN) networks. No changes were found in the Salience Network (SN), a surprising result as the network is involved in the modulation of emotional and fluid reasoning. The insula is crucial hub of the SN and functionally divided in anterior and posterior subregions.

          Methodology

          Using a seed-based approach, we have now analyzed effects of modafinil on the functional connectivity (FC) of insular subregions.

          Principal Findings

          Analysis of FC with resting state fMRI (rs-FMRI) revealed increased FC between the right posterior insula and the putamen, the superior frontal gyrus and the anterior cingulate cortex in the modafinil-treated group.

          Conclusions

          Modafinil is considered a putative cognitive enhancer. The rs-fMRI modifications that we have found are consistent with the drug cognitive enhancing properties and indicate subregional targets of action.

          Trial Registration

          ClinicalTrials.gov NCT01684306

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          Most cited references37

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          FMRI visualization of brain activity during a monetary incentive delay task.

          Comparative studies have implicated striatal and mesial forebrain circuitry in the generation of autonomic, endocrine, and behavioral responses for incentives. Using blood oxygen level-dependent functional magnetic resonance imaging, we sought to visualize functional activation of these regions in 12 normal volunteers as they anticipated and responded for monetary incentives. Both individual and group analyses of time-series data revealed significant activation of striatal and mesial forebrain structures (including insula, caudate, putamen, and mesial prefrontal cortex) during trials involving both monetary rewards and punishments. In addition to these areas, during trials involving punishment, group analysis revealed activation foci in the anterior cingulate and thalamus. These results corroborate comparative studies which implicate striatal and mesial forebrain circuitry in the elaboration of incentive-driven behavior. This report also introduces a new paradigm for probing the functional integrity of this circuitry in humans.
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            The Raven's progressive matrices: change and stability over culture and time.

            J Raven (2000)
            Data relating to the stability and variation in the norms for the Raven's Progressive Matrices Test (a well-validated measure of basic cognitive functioning) for different cultural, ethnic, and socioeconomic groups on a worldwide and within-country basis are first summarized. Subsequent sections deal with variation over time. A possible explanation for the variation in norms over time and between ethnic groups within countries is offered. Copyright 2000 Academic Press.
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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

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                19 September 2014
                : 9
                : 9
                : e107145
                Affiliations
                [1 ]Department of Neuroscience and Imaging, University “G. d'Annunzio” Chieti-Pescara, Chieti, Italy
                [2 ]Molecular Neurology Unit, Center of Excellence on Aging, University “G. d'Annunzio”, Chieti-Pescara, Chieti, Italy
                [3 ]Departments of Neurology and Pharmacology, Institute for Memory Impairments and Neurological Disorders, University of California-Irvine, Irvine, CA, United States of America
                VU University Medical Center, Netherlands
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: NC SLS. Performed the experiments: NC SLS. Analyzed the data: NC AT SLS. Contributed reagents/materials/analysis tools: AT. Contributed to the writing of the manuscript: NC AT SLS.

                Article
                PONE-D-14-17137
                10.1371/journal.pone.0107145
                4169531
                25237810
                6e54cc4d-c795-4c10-9dde-6e2b80807c4a
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 April 2014
                : 3 August 2014
                Page count
                Pages: 12
                Funding
                SLS is supported by funds from the Italian Department of Education [Fondo per gli Investimenti della Ricerca di Base (FIRB) 2003; Programmi di Ricerca di Rilevante Interesse nazionale (PRIN) 2008]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Neuroscience
                Behavioral Neuroscience
                Cognitive Neuroscience
                Learning and Memory
                Neural Networks
                Medicine and Health Sciences
                Neurology
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. Data have been deposited to OpenfMRI and are available at: https://openfmri.org/dataset/ds000133.

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                Uncategorized

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