Brain dynamics of post‐task resting state are influenced by expertise: Insights from baseball players

A musician's nervous system is thought to specialize to their mode of music production. For instance, the pianist's control of hands and arms develops to facilitate greater dexterity at the keyboard, while the cellist develops control to play notes using both the fret board and/or bow. Our previous work, employing an anomalous musical event (AME) detection task, identified neural and behavioral correlates that differentiated between a specific class of musicians, cellists, and those without professional musical training and expertise. Here we investigate a fine-grain differentiation between musicians having different modes of musical production, specifically in terms of how these differences are manifested in the neural correlates identified in the AME task. We show, using electroencephalography (EEG), that both event related potentials (ERPs) and single-trial analysis of the EEG can grade musical expertise by mode of sound production. Important is that these fine-grained EEG correlates are observable absent any motor response or active music production by the individuals. We find evidence that these grades of expertise are mediated by different sensory-motor interactions emblematic of the sound production mode. More broadly, our results show that neural markers can both define types of musical expertise and decompose their source components when behavioral differences are either minute or indistinguishable.

An extraordinary physiological capacity combined with remarkable motor control, perception, and cognitive functioning is crucial for high performance in sports. Tests that assess the physical abilities are already well established. Moreover, a growing area of research evolved in the recent past that is particularly concerned with the basic cognitive functions by means of neurocognitive tests in experts and elite athletes. The aim of this meta-analysis (k = 19) is to quantify differences among experts and nonexperts as well as elite athletes and non-elite athletes. In addition, it aims to assemble and compare previous research and analyze possible differences in cognitive functions depending on age, skill level, and used cognitive tasks. Overall, the mean effect size was small to medium (r = 0.22), indicating superior cognitive functions in experts and elite athletes. The factor of skill definition significantly differentiates the cognition-expertise relationship. In contrast, differences in age groups and cognitive areas appeared but were not significant. Future research should prefer the elite rather than the expert definition and distinguish between high-performance and amateur athletes. Furthermore, the findings suggest that it can be beneficial for coaches and sport clubs to integrate cognitive tests as an additional tool for scouting and for optimizing the athletic development of their players.

The unique architecture of the human connectome is defined initially by genetics and subsequently sculpted over time with experience. Thus, similarities in predisposition and experience that lead to similarities in social, biological, and cognitive attributes should also be reflected in the local architecture of white matter fascicles. Here we employ a method known as local connectome fingerprinting that uses diffusion MRI to measure the fiber-wise characteristics of macroscopic white matter pathways throughout the brain. This fingerprinting approach was applied to a large sample (N=841) of subjects from the Human Connectome Project, revealing a reliable degree of between-subject correlation in the local connectome fingerprints, with a relatively complex, low-dimensional substructure. Using a cross-validated, high-dimensional regression analysis approach, we derived local connectome phenotype (LCP) maps that could reliably predict a subset of subject attributes measured, including demographic, health and cognitive measures. These LCP maps were highly specific to the attribute being predicted but also sensitive to correlations between attributes. Collectively, these results indicate that the local architecture of white matter fascicles reflects a meaningful portion of the variability shared between subjects along several dimensions.