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      Cognitive & motor skill transfer across speeds: A video game study

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      PLoS ONE
      Public Library of Science

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          Abstract

          We examined the detailed behavioral characteristics of transfer of skill and the ability of the adaptive control of thought rational (ACT-R) architecture to account for this with its new Controller module. We employed a simple action video game called Auto Orbit and investigated the control tuning of timing skills across speed perturbations of the environment. In Auto Orbit, players needed to learn to alternate turn and shot actions to blow and burst balloons under time constraints imposed by balloon resets and deflations. Cognitive and motor skill transfer was assessed both in terms of game performance and in terms of the details of their motor actions. We found that skill transfer across speeds necessitated the recalibration of action timing skills. In addition, we found that acquiring skill in Auto Orbit involved a progressive decrease in variability of behavior. Finally, we found that players with higher skill levels tended to be less variable in terms of action chunking and action timing. These findings further shed light on the complex cognitive and motor mechanisms of skill transfer across speeds in complex task environments.

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          Fitting Linear Mixed-Effects Models Using lme4

          Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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            In situ immune response and mechanisms of cell damage in central nervous system of fatal cases microcephaly by Zika virus

            Zika virus (ZIKV) has recently caused a pandemic disease, and many cases of ZIKV infection in pregnant women resulted in abortion, stillbirth, deaths and congenital defects including microcephaly, which now has been proposed as ZIKV congenital syndrome. This study aimed to investigate the in situ immune response profile and mechanisms of neuronal cell damage in fatal Zika microcephaly cases. Brain tissue samples were collected from 15 cases, including 10 microcephalic ZIKV-positive neonates with fatal outcome and five neonatal control flavivirus-negative neonates that died due to other causes, but with preserved central nervous system (CNS) architecture. In microcephaly cases, the histopathological features of the tissue samples were characterized in three CNS areas (meninges, perivascular space, and parenchyma). The changes found were mainly calcification, necrosis, neuronophagy, gliosis, microglial nodules, and inflammatory infiltration of mononuclear cells. The in situ immune response against ZIKV in the CNS of newborns is complex. Despite the predominant expression of Th2 cytokines, other cytokines such as Th1, Th17, Treg, Th9, and Th22 are involved to a lesser extent, but are still likely to participate in the immunopathogenic mechanisms of neural disease in fatal cases of microcephaly caused by ZIKV.
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              Toward an instance theory of automatization.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: InvestigationRole: Software
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                12 October 2021
                2021
                : 16
                : 10
                : e0258242
                Affiliations
                [001] Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
                University of Sydney, AUSTRALIA
                Author notes

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

                Author information
                https://orcid.org/0000-0002-0985-6791
                Article
                PONE-D-21-05223
                10.1371/journal.pone.0258242
                8509974
                34637460
                9cf9eaee-7373-421e-abae-e9ad33c749b5
                © 2021 Gianferrara et al

                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
                : 20 February 2021
                : 23 September 2021
                Page count
                Figures: 9, Tables: 6, Pages: 31
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000006, Office of Naval Research;
                Award ID: N00014-15-1-2151
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100006602, Air Force Research Laboratory;
                Award ID: FA9550-18-1-0251
                Award Recipient :
                This research was supported by the Office of Naval Research ( https://www.onr.navy.mil/) Grant N00014-15-1-2151 to JRA, and by Air Force Research Laboratory (AFOSR/AFRL - https://www.afrl.af.mil/) award FA9550-18-1-0251 to JRA. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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                Custom metadata
                All data and software can be found on the KiltHub public repository. Data are located here: https://doi.org/10.1184/R1/13834643 and software can be accessed here: https://doi.org/10.1184/R1/13836224.

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