Sport, Bewegung, Training und das zentrale Nervensystem

<jats:title>Abstract</jats:title><jats:p>Coordinative challenging exercises in changing environments referred to as open-skill exercises seem to be beneficial on cognitive function. Although electroencephalographic research allows to investigate changes in cortical processing during movement, information about cortical dynamics during open-skill exercise is lacking. Therefore, the present study examines frontal brain activation during table tennis as an open-skill exercise compared to cycling exercise and a cognitive task. 21 healthy young adults conducted three blocks of table tennis, cycling and n-back task. Throughout the experiment, cortical activity was measured using 64-channel EEG system connected to a wireless amplifier. Cortical activity was analyzed calculating theta power (4–7.5 Hz) in frontocentral clusters revealed from independent component analysis. Repeated measures ANOVA was used to identify within subject differences between conditions (table tennis, cycling, n-back; <jats:italic>p</jats:italic> &lt; .05). ANOVA revealed main-effects of condition on theta power in frontal (<jats:italic>p</jats:italic> &lt; .01, <jats:italic>η</jats:italic><jats:sub>p</jats:sub><jats:sup>2</jats:sup> = 0.35) and frontocentral (<jats:italic>p</jats:italic> &lt; .01, <jats:italic>η</jats:italic><jats:sub>p</jats:sub><jats:sup>2</jats:sup> = 0.39) brain areas. Post-hoc tests revealed increased theta power in table tennis compared to cycling in frontal brain areas (<jats:italic>p</jats:italic> &lt; .05, <jats:italic>d</jats:italic> = 1.42). In frontocentral brain areas, theta power was significant higher in table tennis compared to cycling (<jats:italic>p</jats:italic> &lt; .01, <jats:italic>d</jats:italic> = 1.03) and table tennis compared to the cognitive task (<jats:italic>p</jats:italic> &lt; .01, <jats:italic>d</jats:italic> = 1.06). Increases in theta power during continuous table tennis may reflect the increased demands in perception and processing of environmental stimuli during open-skill exercise. This study provides important insights that support the beneficial effect of open-skill exercise on brain function and suggest that using open-skill exercise may serve as an intervention to induce activation of the frontal cortex.</jats:p>

<jats:p> Agility, a key component of team ball sports, describes an athlete´s ability to move fast in response to changing environments. While agility requires basic cognitive functions like processing speed, it also requires more complex cognitive processes like working memory and inhibition. Yet, most agility tests restrict an assessment of cognitive processes to simple reactive times that lack ecological validity. Our aim in this study was to assess agility performance by means of total time on two agility tests with matched motor demands but with both low and high cognitive demands. We tested 22 female team athletes on SpeedCourt, using a simple agility test (SAT) that measured only processing speed and a complex agility test (CAT) that required working memory and inhibition. We found excellent to good reliability for both our SAT (ICC = .79) and CAT (ICC =.70). Lower agility performance on the CAT was associated with increased agility total time and split times ( p &lt; .05). These results demonstrated that agility performance depends on the complexity of cognitive demands. There may be interference-effects between motor and cognitive performances, reducing speed when environmental information becomes more complex. Future studies should consider agility training models that implement complex cognitive stimuli to challenge athletes according to competitive demands. This will also allow scientists and practitioners to tailor tests to talent identification, performance development and injury rehabilitation. </jats:p>

<jats:title>Abstract</jats:title><jats:sec> <jats:title>Purpose</jats:title> <jats:p>Exhaustive cardiovascular load can affect neural processing and is associated with decreases in sensorimotor performance. The purpose of this study was to explore intensity-dependent modulations in brain network efficiency in response to treadmill running assessed from resting-state electroencephalography (EEG) measures.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>Sixteen trained participants were tested for individual peak oxygen uptake (VO<jats:sub>2 peak</jats:sub>) and performed an incremental treadmill exercise at 50% (10 min), 70% (10 min) and 90% speed VO<jats:sub>2 peak</jats:sub> (all-out) followed by cool-down running and active recovery. Before the experiment and after each stage, borg scale (BS), blood lactate concentration (B<jats:sub>La</jats:sub>), resting heartrate (HR<jats:sub>rest</jats:sub>) and 64-channel EEG resting state were assessed. To analyze network efficiency, graph theory was applied to derive small world index (SWI) from EEG data in theta, alpha-1 and alpha-2 frequency bands.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>Analysis of variance for repeated measures revealed significant main effects for intensity on BS, B<jats:sub>La</jats:sub>, HR<jats:sub>rest</jats:sub> and SWI. While BS, B<jats:sub>La</jats:sub> and HR<jats:sub>rest</jats:sub> indicated maxima after all-out, SWI showed a reduction in the theta network after all-out.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusion</jats:title> <jats:p>Our explorative approach suggests intensity-dependent modulations of resting-state brain networks, since exhaustive exercise temporarily reduces brain network efficiency. Resting-state network assessment may prospectively play a role in training monitoring by displaying the readiness and efficiency of the central nervous system in different training situations.</jats:p> </jats:sec>

<jats:title>Abstract </jats:title><jats:p>Mobile Electroencephalography (EEG) provides insights into cortical contributions to postural control. Although changes in theta (4–8 Hz) and alpha frequency power (8–12 Hz) were shown to reflect attentional and sensorimotor processing during balance tasks, information about the effect of stance leg on cortical processing related to postural control is lacking. Therefore, the aim was to examine patterns of cortical activity during single-leg stance with varying surface stability. EEG and force plate data from 21 healthy males (22.43 ± 2.23 years) was recorded during unipedal stance (left/right) on a stable and unstable surface. Using source-space analysis, power spectral density was analyzed in the theta, alpha-1 (8–10 Hz) and alpha-2 (10–12 Hz) frequency bands. Repeated measures ANOVA with the factors leg and surface stability revealed significant interaction effects in the left (<jats:italic>p</jats:italic> = 0.045, <jats:italic>η</jats:italic><jats:sub><jats:italic>p</jats:italic></jats:sub><jats:sup>2</jats:sup> = 0.13) and right motor clusters (<jats:italic>F</jats:italic> = 16.156; <jats:italic>p</jats:italic> = 0.001, <jats:italic>η</jats:italic><jats:sub><jats:italic>p</jats:italic></jats:sub><jats:sup>2</jats:sup> = 0.41). Furthermore, significant main effects for surface stability were observed for the fronto-central cluster (theta), left and right motor (alpha-1), as well as for the right parieto-occipital cluster (alpha-1/alpha-2). Leg dependent changes in alpha-2 power may indicate lateralized patterns of cortical processing in motor areas during single-leg stance. Future studies may therefore consider lateralized patterns of cortical activity for the interpretation of postural deficiencies in unilateral lower limb injuries.</jats:p>

<jats:p>Whereas initial findings have already identified cortical patterns accompanying proprioceptive deficiencies in patients after anterior cruciate ligament reconstruction (ACLR), little is known about compensatory sensorimotor mechanisms for re-establishing postural control. Therefore, the aim of the present study was to explore leg dependent patterns of cortical contributions to postural control in patients 6 weeks following ACLR. A total of 12 patients after ACLR (25.1 ± 3.2 years, 178.1 ± 9.7 cm, 77.5 ± 14.4 kg) and another 12 gender, age, and activity matched healthy controls participated in this study. All subjects performed 10 × 30 s. single leg stances on each leg, equipped with 64-channel mobile electroencephalography (EEG). Postural stability was quantified by area of sway and sway velocity. Estimations of the weighted phase lag index were conducted as a cortical measure of functional connectivity. The findings showed significant group × leg interactions for increased functional connectivity in the anterior cruciate ligament (ACL) injured leg, predominantly including fronto−parietal [<jats:italic>F</jats:italic><jats:sub>(1, 22)</jats:sub> = 8.41, <jats:italic>p</jats:italic> ≤ 0.008, η<jats:sup>2</jats:sup> = 0.28], fronto−occipital [<jats:italic>F</jats:italic><jats:sub>(1, 22)</jats:sub> = 4.43, <jats:italic>p</jats:italic> ≤ 0.047, η<jats:sup>2</jats:sup> = 0.17], parieto−motor [<jats:italic>F</jats:italic><jats:sub>(1, 22)</jats:sub> = 10.30, <jats:italic>p</jats:italic> ≤ 0.004, η<jats:sup>2</jats:sup> = 0.32], occipito−motor [<jats:italic>F</jats:italic><jats:sub>(1, 22)</jats:sub> = 5.21, <jats:italic>p</jats:italic> ≤ 0.032, η<jats:sup>2</jats:sup> = 0.19], and occipito−parietal [<jats:italic>F</jats:italic><jats:sub>(1, 22)</jats:sub> = 4.60, <jats:italic>p</jats:italic> ≤ 0.043, η<jats:sup>2</jats:sup> = 0.17] intra−hemispherical connections in the contralateral hemisphere and occipito−motor [<jats:italic>F</jats:italic><jats:sub>(1, 22)</jats:sub> = 7.33, <jats:italic>p</jats:italic> ≤ 0.013, η<jats:sup>2</jats:sup> = 0.25] on the ipsilateral hemisphere to the injured leg. Higher functional connectivity in patients after ACLR, attained by increased emphasis of functional connections incorporating the somatosensory and visual areas, may serve as a compensatory mechanism to control postural stability of the injured leg in the early phase of rehabilitation. These preliminary results may help to develop new neurophysiological assessments for detecting functional deficiencies after ACLR in the future.</jats:p>