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      Lenticular nucleus volume predicts performance in real‐time strategy game: cross‐sectional and training approach using voxel‐based morphometry

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          Abstract

          It is unclear why some people learn faster than others. We performed two independent studies in which we investigated the neural basis of real‐time strategy (RTS) gaming and neural predictors of RTS game skill acquisition. In the first (cross‐sectional) study, we found that experts in the RTS game StarCraft ® II (SC2) had a larger lenticular nucleus volume (LNV) than non‐RTS players. We followed a cross‐validation procedure where we used the volume of regions identified in the first study to predict the quality of learning a new, complex skill (SC2) in a sample of individuals who were naive to RTS games (a second (training) study). Our findings provide new insights into how the LNV, which is associated with motor as well as cognitive functions, can be utilized to predict successful skill learning and be applied to a much broader context than just video games, such as contributing to optimizing cognitive training interventions.

          Abstract

          In this study, we followed a cross‐validation procedure where we used the volume of regions identified in the first study to predict the quality of learning a new, complex skill (StarCraft ® II) in a sample of individuals who were naive to RTS games (a second (training) study). Our findings provide new insights into how the lenticular nucleus volume, which is associated with motor as well as cognitive functions, can be utilized to predict successful skill learning and be applied to a much broader context than just video games, such as contributing to optimizing cognitive training interventions.

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          G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
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            "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician.

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              Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.

              An anatomical parcellation of the spatially normalized single-subject high-resolution T1 volume provided by the Montreal Neurological Institute (MNI) (D. L. Collins et al., 1998, Trans. Med. Imag. 17, 463-468) was performed. The MNI single-subject main sulci were first delineated and further used as landmarks for the 3D definition of 45 anatomical volumes of interest (AVOI) in each hemisphere. This procedure was performed using a dedicated software which allowed a 3D following of the sulci course on the edited brain. Regions of interest were then drawn manually with the same software every 2 mm on the axial slices of the high-resolution MNI single subject. The 90 AVOI were reconstructed and assigned a label. Using this parcellation method, three procedures to perform the automated anatomical labeling of functional studies are proposed: (1) labeling of an extremum defined by a set of coordinates, (2) percentage of voxels belonging to each of the AVOI intersected by a sphere centered by a set of coordinates, and (3) percentage of voxels belonging to each of the AVOI intersected by an activated cluster. An interface with the Statistical Parametric Mapping package (SPM, J. Ashburner and K. J. Friston, 1999, Hum. Brain Mapp. 7, 254-266) is provided as a freeware to researchers of the neuroimaging community. We believe that this tool is an improvement for the macroscopical labeling of activated area compared to labeling assessed using the Talairach atlas brain in which deformations are well known. However, this tool does not alleviate the need for more sophisticated labeling strategies based on anatomical or cytoarchitectonic probabilistic maps.
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                Author and article information

                Contributors
                nkowalczyk@swps.edu.pl
                Journal
                Ann N Y Acad Sci
                Ann N Y Acad Sci
                10.1111/(ISSN)1749-6632
                NYAS
                Annals of the New York Academy of Sciences
                John Wiley and Sons Inc. (Hoboken )
                0077-8923
                1749-6632
                29 December 2020
                May 2021
                : 1492
                : 1 , Annals Reports ( doiID: 10.1111/nyas.v1492.1 )
                : 42-57
                Affiliations
                [ 1 ] Faculty of Psychology SWPS University of Social Sciences and Humanities Warsaw Poland
                [ 2 ] Institute of Psychology, Polish Academy of Sciences Warsaw Poland
                [ 3 ] Laboratory of Brain Imaging, Neurobiology Center, Nencki Institute of Experimental Biology, Polish Academy of Sciences Warsaw Poland
                [ 4 ] CNS Lab, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences Warsaw Poland
                [ 5 ] Laboratory of Neuroplasticity, Department of Molecular and Cellular Neurobiology Nencki Institute of Experimental Biology, Polish Academy of Sciences Warsaw Poland
                [ 6 ] Department of Neurosurgery Cedars‐Sinai Medical Center Los Angeles California
                Author notes
                [*] [* ]Address for correspondence: Natalia Kowalczyk‐Grębska, Faculty of Psychology, SWPS University of Social Sciences and Humanities, Chodakowska 19/31 Street, 03–815 Warsaw, Poland. nkowalczyk@ 123456swps.edu.pl

                Article
                NYAS14548
                10.1111/nyas.14548
                8246877
                33372699
                7a6cd484-a267-462d-8539-de36eb2688c1
                © 2020 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, LLC on behalf of New York Academy of Sciences

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 05 November 2020
                : 31 August 2020
                : 18 November 2020
                Page count
                Figures: 7, Tables: 0, Pages: 16, Words: 10188
                Funding
                Funded by: Narodowe Centrum Nauki , open-funder-registry 10.13039/501100004281;
                Award ID: 2013/10/E/HS6/00186
                Award ID: 2013/11/N/HS6/01335
                Award ID: 2016/23/B/HS6/03843
                Categories
                Nyasneur1110
                Original Article
                Original Articles
                Custom metadata
                2.0
                May 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:01.07.2021

                Uncategorized
                real‐time strategy games,game performance,training,neuroimaging
                Uncategorized
                real‐time strategy games, game performance, training, neuroimaging

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