Learning to play a musical instrument is a complex task that integrates multiple sensory modalities and higher-order cognitive functions. Therefore, musical training is considered a useful framework for the research on training-induced neuroplasticity. However, the classical nature-or-nurture question remains, whether the differences observed between musicians and non-musicians are due to predispositions or result from the training itself. Here we present a review of recent publications with strong focus on experimental designs to better understand both brain reorganization and the neuronal markers of predispositions when learning to play a musical instrument. Cross-sectional studies identified structural and functional differences between the brains of musicians and non-musicians, especially in regions related to motor control and auditory processing. A few longitudinal studies showed functional changes related to training while listening to and producing music, in the motor network and its connectivity with the auditory system, in line with the outcomes of cross-sectional studies. Parallel changes within the motor system and between the motor and auditory systems were revealed for structural connectivity. In addition, potential predictors of musical learning success were found including increased brain activation in the auditory and motor systems during listening, the microstructure of the arcuate fasciculus, and the functional connectivity between the auditory and the motor systems. We show that “the musical brain” is a product of both the natural human neurodiversity and the training practice.

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 R 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.

Background While research has consistently identified an association between long-term cannabis use and memory impairments, few studies have examined this relationship in a polydrug context (i.e., when combining cannabis with other substances).Aims: In this preliminary study, we used event-related potentials to examine the recognition process in a visual episodic memory task in cannabis users (CU) and cannabis polydrug users (PU). We hypothesized that CU and PU will have both–behavioral and psychophysiological–indicators of memory processes affected, compared to matched non-using controls with the PU expressing more severe changes.Methods 29 non-using controls (CG), 24 CU and 27 PU were enrolled into the study. All participants completed a visual learning recognition task while brain electrical activity was recorded. Event-related potentials were calculated for familiar (old) and new images from a signal recorded during a subsequent recognition test. We used receiver operating characteristic curves for behavioral data analysis.Results The groups did not differ in memory performance based on receiver operating characteristic method in accuracy and discriminability indicators nor mean reaction times for old/new images. The frontal old/new effect expected from prior research was observed for all participants, while a parietal old/new effect was not observed. While, the significant differences in the late parietal component (LPC) amplitude was observed between CG and PU but not between CG and CU nor CU and PU. Linear regression analysis was used to examine the mean amplitude of the LPC component as a predictor of memory performance accuracy indicator. LPC amplitude predicts recognition accuracy only in the CG.Conclusion The results showed alterations in recognition memory processing in CU and PU groups compared to CG, which were not manifested on the behavioral level, and were the most prominent in cannabis polydrug users. We interpret it as a manifestation of the cumulative effect of multiple drug usage in the PU group.