Investigating neural efficiency of elite karate athletes during a mental arithmetic task using EEG

Duru, Adil Deniz; Assem, Moataz

doi:10.1007/s11571-017-9464-y

Cited by 34 publications

(27 citation statements)

References 26 publications

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“…35 However, there is also evidence that, across sports, athletes rely on auditory cues to monitor their own and others’ movements or to respond to cues during competition 1,6,32,36,43 and that neural efficiency, or a reduction in neural activity, has been observed for elite athletes during motor and cognitive tasks. 10,11 Thus, the high auditory processing demands of sports activity may underlie these enhancements. While it may be reasonable to assume that the fitness level of the student-athlete group is greater than the nonathlete group, future studies should be designed to investigate whether fitness level or sport demands underlie the reduction in background noise levels.…”

Section: Discussionmentioning

confidence: 99%

Play Sports for a Quieter Brain: Evidence From Division I Collegiate Athletes

et al. 2019

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Background: Playing sports has many benefits, including boosting physical, cardiovascular, and mental fitness. We tested whether athletic benefits extend to sensory processing—specifically auditory processing—as measured by the frequency-following response (FFR), a scalp-recorded electrophysiological potential that captures neural activity predominately from the auditory midbrain to complex sounds. Hypothesis: Given that FFR amplitude is sensitive to experience, with enrichment enhancing FFRs and injury reducing them, we hypothesized that playing sports is a form of enrichment that results in greater FFR amplitude. Study Design: Cross-sectional study. Level of Evidence: Level 3. Methods: We measured FFRs to the speech syllable “da” in 495 student-athletes across 19 Division I teams and 493 age- and sex-matched controls and compared them on 3 measures of FFR amplitude: amplitude of the response, amplitude of the background noise, and the ratio of these 2 measures. Results: Athletes have larger responses to sound than nonathletes, driven by a reduction in their level of background neural noise. Conclusion: These findings suggest that playing sports increases the gain of an auditory signal by turning down the background noise. This mode of enhancement may be tied to the overall fitness level of athletes and/or the heightened need of an athlete to engage with and respond to auditory stimuli during competition. Clinical Relevance: These results motivate athletics overall and engagement in athletic interventions for populations that struggle with sensory processing, such as individuals with language disorders. Also, because head injuries can disrupt these same auditory processes, it is important to consider how auditory processing enhancements may offset injury.

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Section: Discussionmentioning

confidence: 99%

Play Sports for a Quieter Brain: Evidence From Division I Collegiate Athletes

et al. 2019

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“…Gamma power synchronization has been found in a wide range of cognitive (Bosman, Lansink, & Pennartz, 2014) and sensory operations ( van Ede, Szebényi, & Maris, 2014). Alpha power is mainly involved in cognitive processes (Başar, Schürmann, Başar-Eroglu, & Karakas, 1997;Klimesch, 1999) but modulation of alpha rhythms has been observed also during the elaboration of event-specific sensory and motor information (Babiloni et al, 2016) and is influenced by the specific task and by the individual motor experience (Duru & Assem, 2018). Gamma power synchronization has been found in a wide range of cognitive (Bosman et al, 2014) and sensory operations (van Ede et al, 2014) and has been associated with imagined rather than executed motor actions (Korik, Sosnik, Siddique, & Coyle, 2018).…”

Section: Sensorimotor Integration and Hypnotizabilitymentioning

confidence: 99%

Spectral and topological analyses of the cortical representation of the head position: Does hypnotizability matter?

et al. 2019

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Introduction The aim of this exploratory study was to assess the EEG correlates of head positions (which have never been studied in humans) in participants with different psychophysiological characteristics, as encoded by their hypnotizability scores. This choice is motivated by earlier studies suggesting different processing of vestibular/neck proprioceptive information in subjects with high (highs) and low (lows) hypnotizability scores maintaining their head rotated toward one side ( RH ). Methods We analyzed EEG signals recorded in 20 highs and 19 lows in basal conditions (head forward) and during RH using spectral analysis, which captures changes localized to specific recording sites, and topological data analysis ( TDA ), which instead describes large‐scale differences in processing and representing sensorimotor information. Results Spectral analysis revealed significant differences related to head position for alpha 1, beta 2, beta 3, and gamma bands, but not to hypnotizability. TDA instead revealed global hypnotizability‐related differences in the strengths of the correlations among recording sites during RH . Significant changes were observed in lows on the left parieto‐occipital side and in highs in right frontoparietal region. Significant differences between the two groups were found in the occipital region, where changes were larger in lows than in highs . Conclusions This study reports finding of the EEG correlates of changes in the head posture for the first time, indicating that hypnotizability is related to the head posture representation/processing on large‐scale networks and that spectral and topological data analyses provide complementary results.

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“…EEG data classification is used to identify the mental diseases in emotion recognition and mental state determination using a brain-computer interface (BCI) as well as through the monitoring of mental workload. The basic state that can be identified from the scalp measurements is the resting state of the brain when eyes are open or closed [ 1 ]. The identifiers of these two states are hidden in the frequency content of the measured signal; however, this identifier may also vary in groups of subjects [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Classification of Resting-State Status Based on Sample Entropy and Power Spectrum of Electroencephalography (EEG)

Mohamed

Uçan

Bayat

et al. 2020

Applied Bionics and Biomechanics

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An electroencephalogram (EEG) is a significant source of diagnosing brain issues. It is also a mediator between the external world and the brain, especially in the case of any mental illness; however, it has been widely used to monitor the dynamics of the brain in healthy subjects. This paper discusses the resting state of the brain with eyes open (EO) and eyes closed (EC) by using sixteen channels by the use of conventional frequency bands and entropy of the EEG signal. The Fast Fourier Transform (FFT) and sample entropy (SE) of each sensor are computed as methods of feature extraction. Six classifiers, including logistic regression (LR), K-Nearest Neighbors (KNN), linear discriminant (LD), decision tree (DT), support vector machine (SVM), and Gaussian Naive Bayes (GNB) are used to discriminate the resting states of the brain based on the extracted features. EEG data were epoched with one-second-length windows, and they were used to compute the features to classify EO and EC conditions. Results showed that the LR and SVM classifiers had the highest average classification accuracy (97%). Accuracies of LD, KNN, and DT were 95%, 93%, and 92%, respectively. GNB gained the least accuracy (86%) when conventional frequency bands were used. On the other hand, when SE was used, the average accuracies of SVM, LD, LR, GNB, KNN, and DT algorithms were 92% 90%, 89%, 89%, 86%, and 86%, respectively.

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Investigating neural efficiency of elite karate athletes during a mental arithmetic task using EEG

Cited by 34 publications

References 26 publications

Play Sports for a Quieter Brain: Evidence From Division I Collegiate Athletes

Play Sports for a Quieter Brain: Evidence From Division I Collegiate Athletes

Spectral and topological analyses of the cortical representation of the head position: Does hypnotizability matter?

Classification of Resting-State Status Based on Sample Entropy and Power Spectrum of Electroencephalography (EEG)

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