Single bout of exercise can improve the performance on cognitive tasks. However, cognitive responses may be controversial due to different type, intensity, and duration of exercise. In addition, the mechanism of the effect of acute exercise on brain is still unclear. This study was aimed to investigate the effects of supramaximal exercise on cognitive tasks by means of brain oxygenation monitoring. The brain oxygenation of Prefrontal cortex (PFC) was measured on 35 healthy male volunteers via functional near infrared spectroscopy (fNIRS) system. Subjects performed 2-Back test before and after the supramaximal exercise wingate anerobic test (WAnT) lasting 30-s on cycle ergometer. The PFC oxygenation change evaluation revealed that PFC oxygenation rise during post-exercise 2-Back task was considerably higher than those in pre-exercise 2-Back task. In order to describe the relationship between oxygenation change and exercise performance, subjects were divided into two groups as high performers (HP) and low performers (LP) according to their peak power values (PP) obtained from the supramaximal test. The oxy-hemoglobin (oxy-Hb) values were compared between pre- and post-exercise conditions within subjects and also between subjects according to peak power. When performers were compared, in the HP group, the oxy-Hb values in post-exercise 2-Back test were significantly higher than those in pre-exercise 2-Back test. HP had significantly higher post-exercise oxy-Hb change (Δ) than those of LP. In addition, PP of the total group were significantly correlated with Δoxy-Hb.The key findings of the present study revealed that acute supramaximal exercise has an impact on the brain oxygenation during a cognitive task. Also, the higher the anerobic PP describes the larger the oxy-Hb response in post-exercise cognitive task. The current study also demonstrated a significant correlation between peak power (exercise load) and post-exercise hemodynamic responses (oxy-, deoxy- and total-Hb). The magnitude of this impact might be related with the physical performance capacities of the individuals. This can become a valuable parameter for future studies on human factor.

This study compared the hemodynamic changes in the prefrontal cortex during sprint interval training (SIT) and recovery periods in sedentary and athletes. SIT was performed on a cycling ergometer on 12 male athletes and 9 sedentary participants. A functional near-infrared spectroscopy (fNIRS) device was used to record the hemodynamic changes of the prefrontal cortex throughout the protocol. The oxyhemoglobin (Oxy-Hb) levels in the prefrontal cortex were increased significantly, and the power outputs were decreased in repetitive Wingate anaerobic tests (WAnTs) in Sedentary and Athletes group (p < 0.001). In addition, the Sedentary group had higher Oxy-Hb values (p < 0.001). However, the recovery times decreased significantly after all WAnTs (p < 0.05). Despite the increased fatigue, athletes performed better with less Oxy-Hb than the sedentary participants. Also, the recovery of the Oxy-Hb values in the prefrontal region was faster in athletes. These results may highlight a possible brain adaptation in athletes.

The question of when the optimal effect of warm-up is reached after the warm-up phase in swimming compe- titions is still not fully elucidated. The purpose of this study was to see how self-selected active rest in three dif- ferent duration periods affected 100-m maximum swimming performance. Eight well-trained elite swimmers (6 males and 2 females, mean age: 17.2 ± 3, mean 616 FINA points) were included in the study. After the participants completed a standard warm-up consisting of dryland-based dynamic warm-up (10-min) and in-water warm-up protocols (1200-m / ~25-min) in 3 different sessions, they observed different transition phase periods (15, 30 and 45-min) with standard clothes in their maximum heart rate of 30% and self-selected movement forms (stretching, walking, etc.) completed by active rest. Subsequently, swimmers carried out the 100-m maximum time-trial swim test using their main stroke. Tympanic temperature (Ttympanic), forehead temperature (Tforehead), heart rate (HR), rating of perceived exertion (RPE), and maximal 100-m-time-trial (TT) were recorded during all sessions. Measurements were evaluated in repeated measures ANOVA. Delta (Δ) calculation was used to score changes and strengthen the analysis. The 100-m time-trial demonstrated a trend of improvement in 30-min active rest (p=0.037). In addition, there was no difference between rest times in Tforehead, Ttympanic, HR, and RPE conditions (p>0.05). The 30-min active rest interval improved 100-m swimming performance by 1.6% and 0.8% compared to 15-min and 45-min active rest. The positive effect of pool warm-up can be maintained for up to 30 minutes with self-paced active rest.

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The aim of this study is to examine the feeling of being stuck and phone addiction levels of student participants in Manisa Celal Bayar University Faculty of Sport Sciences. In the study, the convenience sampling model, which is one of the quantitative research methods, was used as a research method. The study group of the research consists of 97 female and 193 male students from Manisa Celal Bayar University Faculty of Sport Sciences. Personal information form prepared by the researcher, Smartphone Addiction (Short Form) scale and Feeling Stuck scale were used as data collection tools in the research. SPSS 25.0 package program was used in the analysis of the data. While the kurtosis and skewness values (+1.5 and -1.5) are taken into account in the normality test analyzes (Tabachnick & Fidell, 2013); Levene test was used for homogeneity test. Independent T test was used for pairwise comparisons, one of the parametric tests for normally distributed values, and One Way Anova test was used for more than two encounters. In addition, Pearson correlation analysis was used. Research findings showed that an average of 51% of female participants and 19% of male participants were addicted to smartphones. A significant difference was found in the comparison of smartphone addiction scores between genders (p

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