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      Neural correlates of self- and other-referential processing in young adolescents and the effects of testosterone and peer similarity

      , , , , , ,
      NeuroImage
      Elsevier BV

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          Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.

          Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements. Copyright © 2011 Elsevier Inc. All rights reserved.
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            A self-report measure of pubertal status: Reliability, validity, and initial norms.

            Puberty is a central process in the complex set of changes that constitutes the transition from childhood to adolescence. Research on the role of pubertal change in this transition has been impeded by the difficulty of assessing puberty in ways acceptable to young adolescents and others involved. Addressing this problem, this paper describes and presents norms for a selfreport measure of pubertal status. The measure was used twice annually over a period of three years in a longitudinal study of 335 young adolescent boys and girls. Data on a longitudinal subsample of 253 subjects are reported. The scale shows good reliability, as indicated by coefficient alpha. In addition, several sources of data suggest that these reports are valid. The availability of such a measure is important for studies, such as those based in schools, in which more direct measures of puberty may not be possible.
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              Multi-task connectivity reveals flexible hubs for adaptive task control

              Extensive evidence suggests the human ability to adaptively implement a wide variety of tasks is preferentially due to the operation of a fronto-parietal brain network. We hypothesized that this network’s adaptability is made possible by ‘flexible hubs’ – brain regions that rapidly update their pattern of global functional connectivity according to task demands. We utilized recent advances in characterizing brain network organization and dynamics to identify mechanisms consistent with the flexible hub theory. We found that the fronto-parietal network’s brain-wide functional connectivity pattern shifted more than other networks’ across a variety of task states, and that these connectivity patterns could be used to identify the current task. Further, these patterns were consistent across practiced and novel tasks, suggesting reuse of flexible hub connectivity patterns facilitates adaptive (novel) task performance. Together, these findings support a central role for fronto-parietal flexible hubs in cognitive control and adaptive implementation of task demands generally.
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                Author and article information

                Contributors
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                Journal
                NeuroImage
                NeuroImage
                Elsevier BV
                10538119
                October 2020
                October 2020
                : 219
                : 117060
                Article
                10.1016/j.neuroimage.2020.117060
                32561475
                675481f8-ed6d-47ec-a180-4c63dc039b93
                © 2020

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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