Our brain orchestrates about 85 billion nerve cells as well as non-neural cells1, wired via the utterly exceptional number of a hundred trillions of synapses2,3 - an endless playground for intriguing dynamic processes in the brain, known as neuroplasticity including all of its facets and varieties4.

Neuroplasticity is certainly among the most fascinating phenomena in the field of neurosciences, especially because it exemplifies the high sensitivity of the brain towards environmental demands. However, despite the large progress that has been achieved in animal and human studies dealing with brain plasticity changes as a result of learning in the past decades, our knowledge about the manifold mechanisms underlying neural changes due to skill acquisition is still at a very early stage. The groundbreaking findings5 of altered hippocampi found in experienced London taxi drivers are among the first ones demonstrating that specific daily routines – or in a broader sense learning – alter structural characteristics of the brain. Since then, a considerable number of studies investigating structural brain changes as a result of skill acquisition were conducted in various domains, including second language acquisition and proficiency6,7, juggling8, the domain of musical expertise9,10, and especially also the clinical neurological domain11. Furthermore, even a physical leisure activity can induce structural brain changes12.

Most of these seminal studies focused on experience-dependent changes in gray matter (GM) volume, while more recent studies in this field are also looking at other imaging parameters such as white matter (WM) microstructure in order to assess the manifold ways of how the brain adapts to environmental demands13,14,15,16. While these studies provided further important insights into experience-dependent changes of the brain, combined approaches utilizing multimodal imaging parameters within one and the same experimental design are comparatively rare11,13,16,17. Particularly the fact that learning processes may alter certain characteristics of GM or WM morphology in different ways, each of them occurring with different shape, strength, and latency14,18, clearly indicates the necessity to apply longitudinal multimodal imaging parameters to adequately map the manifold dynamics of the brain’s capacity to adapt to environmental stimulation.

This study took an important step towards this direction. In a longitudinal multimodal neuroimaging study involving a pre- post-test design with a professionally supervised 3-week unicycling training in between, and a subsequent follow-up assessment five weeks after the training, we investigated dynamic neural changes implicated in the learning process of a highly complex balance task. We focused on unicycling since this skill is one of the most complex balance tasks someone can learn as one constantly needs to adjust the balance19 both forth-back and left-right. At the same time, one needs to pay attention to the muscle force in the feet, to the right speed and pedal rotation frequency. Finally and equally important, one must be aware of the own spatial movements while sitting on a unicycle, requiring sophisticated and skillful feedback from the senses to the whole body motion to adequately operate a unicycle20.

There are several studies investigating the effects of balance training on both structural and functional characteristics of the brain, especially in clinical samples and in samples involving older adults. Sehm et al.21, for instance, administered a whole-body dynamic balancing task in a sample of patients with Parkinson’s disease over a time period of six weeks. They found improvements in balancing ability, which were correlated with changes in GM in brain regions putatively implicated in the coordination of complex body movements (such as the left inferior parietal cortex, the left ventral premotor cortex, or the left middle temporal gyrus). A recent fMRI study22 employed a 5 weeks classical balance training (standing with one leg on different unstable grounds) in older adults and found reduced brain activity in regions associated with postural control, in which typically over-activations with increasing age have been found.

In a sample of adults from the normal population, Rogge et al.23 found improvements in memory and spatial cognition as a result of a balance training conducted over a time period of 12 weeks. The balance training was also associated with widespread changes in cortical thickness in regions supporting visual and vestibular self-motion perception such as the superior temporal gyrus, visual association cortices, the precentral gyri, or the putamen24. Significant structural brain changes were observed even after exercising for only two sessions with a complex whole-body balancing task16. Strikingly, that study revealed substantial training-induced increases in GM in frontal and parietal brain regions, accompanied by significant decreases in Fractional Anisotropy (FA) in partly overlapping brain regions. More recently, the same group found that a single balance training session resulted in localized increases in cortical thickness in the motor cortex25.

Taken together, these studies provide converging evidence that the brain is highly sensitive to learning a motor related or balance task, even after a very short period of time25. What is still not well understood in relevant literature is how different types of brain tissue (such as GM and WM morphology) alter in response to the very same learning task (among the rare exceptions is a longitudinal balance training study16). For instance, to which extent are significant training-induced changes in GM morphology (GM volume, cortical thickness) related to corresponding changes in WM integrity? Does a motor skill training differentially affect measures of GM volume and cortical thickness? Does the motor training yield brain changes only in motor brain regions (such as the primary motor cortex or the corticospinal tract), or in regions supporting visual and spatial cognition as well? This multimodal imaging study was designed to address some of these important questions which received comparatively less attention so far. We focused on learning to ride a unicycle since this skill is certainly among the most complex balance tasks and hence very likely to induce manifold structural changes in the brain. Another advantage of this task is that participants with no relevant history/experience in this specific ability (i.e., to ride a unicycle) can be tested, therewith providing perfectly equal starting levels for all participants. In addition, learning to ride a unicycle may also constitute an ecologically highly valid approach to improve balancing ability, therewith increasing task commitment and training motivation. On a more general level, brain changes as a result of unicycling may also add evidence to the nascent field of research investigating the role of different kind physical activity interventions (e.g., aerobic training vs. stretching exercises) on cognitive and brain functions26.

Changes in brain structure as a result of the unicycling training were assessed by using T1-weighted images for voxel-based analyses of GM and cortical thickness (CT), and diffusion-weighted images for tensor-based morphometry analyses. It was hypothesized that learning to ride a unicycle affects – along with improvements in behaviorally assessed postural control – different types of brain tissue in several functionally relevant neural circuits, especially in networks supporting motor related functions (such as the motor cortex or the corticospinal tract). Relevant literature further leads us to expect that a complex balance training yields significant structural brain changes in regions supporting cognitive functions (e.g., visual or spatial cognition) as well16,23,24. We further expect that each imaging modality elucidates shared and specific dynamic brain properties underlying this highly complex process, therewith providing further important insights into learning-induced plasticity changes of the brain. Taubert and coworkers27 moreover noted that it is often unclear whether or to which extent alterations in brain structure are linked with individual learning success. Hence, this study also assessed the performance of unicycling after the training which was linked to training-induced changes in brain structure.