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The human brain shows neuroplastic adaptations caused by motor skill training. Of note, there is little known about the plastic architecture of the whole-brain network in resting state. The purpose of the present study was to detect how motor training affected the density distribution of whole-brain resting-state functional connectivity (FC). Resting-state functional magnetic resonance imaging data was assessed based on a comparison of fast-ball student athletes (SA) and non-athlete healthy controls (NC). The voxel-wise data-driven graph theory approach, global functional connectivity density (gFCD) mapping, was applied. Results showed that the SA group exhibited significantly decreased gFCD in brain regions centered at the left triangular part of the inferior frontal gyrus (IFG), extending to the opercular part of the left IFG and middle frontal gyrus compared to the NC group. In addition, findings suggested the idea of an increased neural efficiency of athletes' brain regions associated with attentional-motor modulation and executive control. Furthermore, behavioral results showed that in the SA group, faster executive control reaction time relates to smaller gFCD values in the left IFG. These findings suggested that the motor training would decrease the numbers of FC in IFG to accelerate the executive control with high attentional demands and enable SA to rapidly focus the attention to detect the intriguing target.

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This study explored how the neural efficiency and proficiency worked in athletes with different skill levels from the perspective of effective connectivity brain network in resting state. The deconvolved conditioned Granger causality (GC) analysis was applied to functional magnetic resonance imaging (fMRI) data of 35 elite athletes (EAs) and 42 student‐athletes (SAs) of racket sports as well as 39 normal controls (NCs), to obtain the voxel‐wised hemodynamic response function (HRF) parameters representing the functional segregation and effective connectivity representing the functional integration. The results showed decreased time‐to‐peak of HRF in the visual attention brain regions in the two athlete groups compared with NC and decreased response height in the advanced motor control brain regions in EA comparing to the nonelite groups, suggesting the neural efficiency represented by the regional HRF was different in early and advanced skill levels. GC analysis demonstrated that the GC values within the middle occipital gyrus had a linear trend from negative to positive, suggesting a stepwise “neural proficiency” of the effective connectivity from NC to SA then to EA. The GC values of the inter‐lobe circuits in EA had the trend to regress to NC levels, in agreement with the neural efficiency of these circuits in EA. Further feature selection approach suggested the important role of the cerebral‐brainstem GC circuit for discriminating EA. Our findings gave new insight into the complementary neural mechanisms in brain functional segregation and integration, which was associated with early and advanced skill levels in athletes of racket sports.

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To obtain subdecimeter level accuracy in relative kinematic positioning, the use of double differenced GPS carrier phase measurement with carrier phase ambiguities fixed to their correct integer values must be adopted. If multiple platforms are available in the configuration, the redundancy provided by the multiplicity of platforms can speed up the time to integer ambiguity fixing while at the same time improve the reliability of the solution. An approach to effectively construct ambiguity constraints through the multiplicity of platforms is presented herein. The use of these ambiguity constraints to position multiple moving platforms with respect to each other is then discussed. A series of simulations and field tests are designed and conducted to investigate the effects of different system parameters on this approach, with a configuration of up to 10 moving platforms.The test results show that the use of ambiguity constraints can improve the time to integer ambiguity fixing by up to 67%, relative to the case when no constraints are used. In addition, the use of ambiguity constraints is found to enhance the ability of the multiple platform system to detect wrong ambiguity fixes.