Article

Neurophysiological and autonomic responses of high and low level chess players during difficult and easy chess endgames – A quantitative EEG and HRV study

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  • Escola Superior de Saúde Politécnico de Leiria
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Abstract

The aim of the present study was to analyze the heart rate variability (HRV) and the electroencephalographic (EEG) power spectrum in low and high performance chess players during easy and difficult chess endgames. A total of 28 chess players participated in this cross-sectional study. Participants were divided into two groups according to their ELO level (rating system used by the international chess federation): 1) high level chess players (more than 1600 of ELO score); and 2) low level chess players (ELO less than 1599 of ELO score). Chess players had to complete two easy and two difficult endgames while the electroencephalographic activity and heart rate variability were assessed. High level chess players exhibit more alpha EEG power spectrums (p-value>0.05) during difficult than during easy chess endgames in the occipital area (O1 and O2 electrodes). Moreover, high performance players showed a reduced autonomic modulation (p-value>0.05) during the difficult chess endgames which low performance players did not reach. These results could suggest that high level chess players adapt their neurophysiological response to the task demand.

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... In this regard, previous studies showed that theta power spectrum (4-7 Hz), which has been related to mental effort [13][14][15][16][17], was increased when the level of difficulty increased [10][11][12]. In the same line, chess players exhibit a higher Alpha power spectrum (8)(9)(10)(11)(12) during difficult chess endgames [12] and higher-skilled opponents [18]. Furthermore, beta power spectrum (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) has been suggested to be behavioral arousal and attentional process biomarker [19]. ...
... In the same line, chess players exhibit a higher Alpha power spectrum (8)(9)(10)(11)(12) during difficult chess endgames [12] and higher-skilled opponents [18]. Furthermore, beta power spectrum (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) has been suggested to be behavioral arousal and attentional process biomarker [19]. ...
... In this regard, expert chess players showed higher task-related functional integration of the cortical areas [3], superior pattern recognition, and memory retrieval of chunks [22] when compared with novices. Similarly, high-level chess players exhibit greater values of Alpha power spectrum than low-level chess players during high demanding tasks [18]. ...
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... Convergent cross mapping analysis demonstrated the correlation between IMF envelop of EEG and HRV, and surrogate data analysis confirmed the statistical significance of nonlinear metrics estimated from them [4]. HRV and EEG N. Bahador spectral measures were compared in some studies [5]. Relationship between sample entropy extracted from HRV and Wiener entropy extracted from EEG was also investigated [6]. ...
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... Regarding the performance in sports, the analysis of the cortical electrical activity through the electroencephalographic (EEG) signal may be a useful alternative to assess the activation of professional female soccer players before a competition [1] and to monitor stress or cognitive load in chess players while playing games at different paces or solving chess problems or endgames with different difficulty levels [2,3,4]. Similarly, in the military context, this tool can be considered for training purposes during takeoff, landing, air-air attacks, and air-ground attack maneuvers [5]. ...
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Electrical potentials produced by blinks and eye movements present serious problems for electroencephalographic (EEG) and event-related potential (ERP) data interpretation and analysis, particularly for analysis of data from some clinical populations. Often, all epochs contaminated by large eye artifacts are rejected as unusable, though this may prove unacceptable when blinks and eye movements occur frequently. Frontal channels are often used as reference signals to regress out eye artifacts, but inevitably portions of relevant EEG signals also appearing in EOG channels are thereby eliminated or mixed into other scalp channels. A generally applicable adaptive method for removing artifacts from EEG records based on blind source separation by independent component analysis (ICA) (Neural Computation 7 (1995) 1129; Neural Computation 10(8) (1998) 2103; Neural Computation 11(2) (1999) 606) overcomes these limitations. Results on EEG data collected from 28 normal controls and 22 clinical subjects performing a visual selective attention task show that ICA can be used to effectively detect, separate and remove ocular artifacts from even strongly contaminated EEG recordings. The results compare favorably to those obtained using rejection or regression methods. The ICA method can preserve ERP contributions from all of the recorded trials and all the recorded data channels, even when none of the single trials are artifact-free.
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Recent theoretical work has suggested that brain oscillations in the theta band are involved in active maintenance and recall of working memory representations. To test this theoretical framework we recorded neuromagnetic responses from 10 subjects performing the Sternberg task. Subjects were required to retain a list of 1, 3, 5 or 7 visually presented digits during a 3-s retention period. During the retention period we observed ongoing frontal theta activity in the 7-8.5-Hz band recorded by sensors over frontal brain areas. The activity in the theta band increased parametrically with the number of items retained in working memory. A time-frequency analysis revealed that the task-dependent theta was present during the retention period and during memory scanning. Following the memory task the theta activity was reduced. These results suggest that theta oscillations generated in frontal brain regions play an active role in memory maintenance.
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Chess is a game that involves many aspects of high level cognition and requires sophisticated problem solving skills. However, there is little understanding of the neural basis of chess cognition. This study employed functional magnetic resonance imaging (fMRI) to identify cortical areas that are active during the analysis of chess positions compared with a spatial task with matched visual stimuli. Bilateral activation was revealed in the superior frontal lobes, the parietal lobes, and occipital lobes. Some small areas of activation were observed unilaterally in the left hemisphere. The left hemisphere showed more activation than the right. Results are discussed in relation to a similar brain imaging study on the game Go.