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Neurofeedback training for young atlete
Poster Abstracts / International Journal of Psychophysiology 85 (2012) 361–430
through the posterior corpus callosum region and occipital lobes are connected through the splenial corpus callosum region. We calculated non-parametric correlations (Spearman, p b .01) between individual behavioral and anatomical measurements. Overall corpus callosum size correlates positively with verbal memory capacity (R = .68) and semantic coding test performance (R = .43). Increase of corpus callosum size also results in decrease of errors in visuo-spatial memory test performance (R= −.52). The size of anterior corpus callosum region correlates negatively with the amount of semantic errors in semantic coding test (R = −.39). Increase of posterior corpus callosum region is related to decrease of errors in verbal memory permanency tests (R = −.56). Furthermore, the size of posterior corpus callosum region correlates negatively with the amount of perseverations in visual memory test (R = −.44). Significant correlations were also revealed between splenial corpus callosum region size and ‘Pictograms’ test performance (R = .42). The revealed patterns demonstrate the role of interhemispheric connections in memory processes. The results suggest rostro-splenial specialization of corpus callosum. Thus, rostral and medial corpus callosum regions mostly determine verbal coding, whereas splenial corpus callosum region is responsible for non-verbal coding in memory. doi:10.1016/j.ijpsycho.2012.07.092
Neurofeedback training for young atlete A. V. Kovalevaa, A. V. Kvitchastyyb, K. Bochaverb, V.N. Kasatkinb a Moscow State University of Psychology and Education, Russia b Sports Psychology Department of the Moscow Sports Committee, Russia Neuromodulation by means of electroencephalography biofeedback (neurofeedback) is used to promote self-regulation. This general method has been applied in a variety of neurobehavioral problems and disorders. Neurofeedback is also used in peak performance training, to optimize cognitive and affective status in the absence of clinical diagnosis. When quantitative EEG (QEEG) is available as part of client assessment, it is possible to measure neurophysiological activity directly. There are patterns that can be identified that implicate dysfunctional localized regional processing, and these patterns can be used to guide neurofeedback intervention (Johnstone, 2008). Young athletes often have mild to serious problems with their psychological state, especially during championships and games. So, we supposed that neurofeedback training must help them to control their mind and body interactions without any drugs and medications. We carried out five neurofeedback trainings with 20 college students (athletes 16–19 years old). EEG was recorded from left and right occipital areas during 15 min of relaxation. Alpha-rhythm power was transformed into the line on the screen. The instruction was to sit with eyes closed and to reach a relaxed state and try to enhance their alpha-rhythm index (line on the screen) during the relaxation period. To reach relaxed state students had to use diaphragmatic breathing. It is a very good method for breathing and relaxation because it allows the most efficient exchange of oxygen and carbon dioxide with the least effort. It also helps enhance general relaxation. Also anxiety level (Spielberger scale) and self-reports was collected before and after neurofeedback training. Alpha, beta and theta power were calculated at the beginning and at the end of each session. Statistical analysis was done using SPSS software package (descriptive statistics, Spearman correlation, Mann–Whitney U-test, Fisher test). Athletes showed a trend toward decreased beta power and increased alpha power from beginning to end of the relaxation period. According to correlation analysis there were a lot of significant
397
correlation between brain activity and anxiety level in male sportsmen, but no significant correlations in females. We also found a decrease of the reactive anxiety only in males. According to the self-reports, most of students noticed some effects of the training: they became more concentrated, less anxious, had better sleep and some of them forgot about headaches. Differences between male and female students might be explained by the fact that females' hormonal fluctuations influence their psychological state and neurofeedback effectiveness (Bazanova et al, 2006, 2008). These results suggests that EEG-neurofeedback can positively influence the psychological state (reduce reactive anxiety), sports performance and wellness of the students, but we should take into account individual characteristics, such as day of the menstrual cycle for females and baseline EEG parameters for everybody. doi:10.1016/j.ijpsycho.2012.07.093
EEG coherence as an index to hypnotizability level A.V. Kirenskayaa, V.Y. Novototsky-Vlasova, V.M. Zvonikovb a Serbsky National Research Centre for Social and Forensic Psychiatry, Russia b Moscow University for the Humanities, Moscow, Russia Methodological clarity. The level of hypnotizability (H) is a stable personality trait that correlates with sustained attentional abilities, vividness of imagery, fantasy proneness, creativity, and emotionality (Crawford, 1989; Crawford, Brown, and Moon, 1993; Crawford, Kapelis, and Harrison, 1995; Crowson Conroy, and Chester, 1991; Gruzelier, 2002). However, H neural mechanisms remain largely unknown. Numerous studies have examined the relationship between EEG measures and H, but EEG results obtained in different studies are controversial. The influence of H level on binding processes has not been studied yet. The application of coherence analysis to EEG data has proven itself a promising tool to investigate rhythmic, large-scale properties of EEG signals and to study the interaction between different cortical networks (Sauseng and Klimesch, 2008). The aim of the present study was to investigate EEG correlates and neural underpinnings of hypnotizability using the coherence analysis. H level was assessed using modified version (including 6 items) of the Stanford Hypnotic Susceptibility Scale (SHSS: C) (Crawford, Allen, 1982). 19 high (HH), 12 medium (MH) and 12 low hypnotizable (LH) persons (14 men, 29 women) were selected for the study. EEG from 19 electrodes was recorded in eyes closed rest condition, and EEG coherence (COH) for 171 electrode pairs (EPs) was analyzed. 10 frequency ranges were used: delta (1–3.5 Hz), theta1 (3.5–6 Hz), theta2 (6–8 Hz), alpha1 (8–10 Hz), alpha2 (10–11.5 Hz), alpha3 (11.5–13 Hz), beta1 (14–19 Hz), beta2 (19–27 Hz), gamma1 (27– 40 Hz), and gamma2 (41–59 Hz). For the evaluation of significant COH differences between groups Mann–Whitney U-test was used. The accepted level of significance was 99% and 99.9%. The COH analysis showed clearly marked differences between HH and LH participants. The COH between distributed brain regions was considerably higher in HH group within delta, theta1, theta2, alpha1, alpha2 and alpha3 frequency bands as compared to LH group. For example, in theta1 range COH values exceeding 0.5 were revealed for 16% EPs in HH group and for 0.5% EPs in LH, and in alpha1 range — for 50% EPs in HH group and for 29% EPs in LH group. The maximal number of electrode pairs with coherence level significantly higher in the group HH compared to LH one was found within theta1 (142 pairs), theta2 (165 pairs) and alpha3 (131 pairs) frequency ranges. Within high frequency bands higher COH was observed in LH group in comparison with HH one — for 74 electrode pairs in beta2 range and for 70 pairs in gamma1 range. In MH group COH values were intermediate between those of HH and LH groups within the whole frequency range.
through the posterior corpus callosum region and occipital lobes are connected through the splenial corpus callosum region. We calculated non-parametric correlations (Spearman, p b .01) between individual behavioral and anatomical measurements. Overall corpus callosum size correlates positively with verbal memory capacity (R = .68) and semantic coding test performance (R = .43). Increase of corpus callosum size also results in decrease of errors in visuo-spatial memory test performance (R= −.52). The size of anterior corpus callosum region correlates negatively with the amount of semantic errors in semantic coding test (R = −.39). Increase of posterior corpus callosum region is related to decrease of errors in verbal memory permanency tests (R = −.56). Furthermore, the size of posterior corpus callosum region correlates negatively with the amount of perseverations in visual memory test (R = −.44). Significant correlations were also revealed between splenial corpus callosum region size and ‘Pictograms’ test performance (R = .42). The revealed patterns demonstrate the role of interhemispheric connections in memory processes. The results suggest rostro-splenial specialization of corpus callosum. Thus, rostral and medial corpus callosum regions mostly determine verbal coding, whereas splenial corpus callosum region is responsible for non-verbal coding in memory. doi:10.1016/j.ijpsycho.2012.07.092
Neurofeedback training for young atlete A. V. Kovalevaa, A. V. Kvitchastyyb, K. Bochaverb, V.N. Kasatkinb a Moscow State University of Psychology and Education, Russia b Sports Psychology Department of the Moscow Sports Committee, Russia Neuromodulation by means of electroencephalography biofeedback (neurofeedback) is used to promote self-regulation. This general method has been applied in a variety of neurobehavioral problems and disorders. Neurofeedback is also used in peak performance training, to optimize cognitive and affective status in the absence of clinical diagnosis. When quantitative EEG (QEEG) is available as part of client assessment, it is possible to measure neurophysiological activity directly. There are patterns that can be identified that implicate dysfunctional localized regional processing, and these patterns can be used to guide neurofeedback intervention (Johnstone, 2008). Young athletes often have mild to serious problems with their psychological state, especially during championships and games. So, we supposed that neurofeedback training must help them to control their mind and body interactions without any drugs and medications. We carried out five neurofeedback trainings with 20 college students (athletes 16–19 years old). EEG was recorded from left and right occipital areas during 15 min of relaxation. Alpha-rhythm power was transformed into the line on the screen. The instruction was to sit with eyes closed and to reach a relaxed state and try to enhance their alpha-rhythm index (line on the screen) during the relaxation period. To reach relaxed state students had to use diaphragmatic breathing. It is a very good method for breathing and relaxation because it allows the most efficient exchange of oxygen and carbon dioxide with the least effort. It also helps enhance general relaxation. Also anxiety level (Spielberger scale) and self-reports was collected before and after neurofeedback training. Alpha, beta and theta power were calculated at the beginning and at the end of each session. Statistical analysis was done using SPSS software package (descriptive statistics, Spearman correlation, Mann–Whitney U-test, Fisher test). Athletes showed a trend toward decreased beta power and increased alpha power from beginning to end of the relaxation period. According to correlation analysis there were a lot of significant
397
correlation between brain activity and anxiety level in male sportsmen, but no significant correlations in females. We also found a decrease of the reactive anxiety only in males. According to the self-reports, most of students noticed some effects of the training: they became more concentrated, less anxious, had better sleep and some of them forgot about headaches. Differences between male and female students might be explained by the fact that females' hormonal fluctuations influence their psychological state and neurofeedback effectiveness (Bazanova et al, 2006, 2008). These results suggests that EEG-neurofeedback can positively influence the psychological state (reduce reactive anxiety), sports performance and wellness of the students, but we should take into account individual characteristics, such as day of the menstrual cycle for females and baseline EEG parameters for everybody. doi:10.1016/j.ijpsycho.2012.07.093
EEG coherence as an index to hypnotizability level A.V. Kirenskayaa, V.Y. Novototsky-Vlasova, V.M. Zvonikovb a Serbsky National Research Centre for Social and Forensic Psychiatry, Russia b Moscow University for the Humanities, Moscow, Russia Methodological clarity. The level of hypnotizability (H) is a stable personality trait that correlates with sustained attentional abilities, vividness of imagery, fantasy proneness, creativity, and emotionality (Crawford, 1989; Crawford, Brown, and Moon, 1993; Crawford, Kapelis, and Harrison, 1995; Crowson Conroy, and Chester, 1991; Gruzelier, 2002). However, H neural mechanisms remain largely unknown. Numerous studies have examined the relationship between EEG measures and H, but EEG results obtained in different studies are controversial. The influence of H level on binding processes has not been studied yet. The application of coherence analysis to EEG data has proven itself a promising tool to investigate rhythmic, large-scale properties of EEG signals and to study the interaction between different cortical networks (Sauseng and Klimesch, 2008). The aim of the present study was to investigate EEG correlates and neural underpinnings of hypnotizability using the coherence analysis. H level was assessed using modified version (including 6 items) of the Stanford Hypnotic Susceptibility Scale (SHSS: C) (Crawford, Allen, 1982). 19 high (HH), 12 medium (MH) and 12 low hypnotizable (LH) persons (14 men, 29 women) were selected for the study. EEG from 19 electrodes was recorded in eyes closed rest condition, and EEG coherence (COH) for 171 electrode pairs (EPs) was analyzed. 10 frequency ranges were used: delta (1–3.5 Hz), theta1 (3.5–6 Hz), theta2 (6–8 Hz), alpha1 (8–10 Hz), alpha2 (10–11.5 Hz), alpha3 (11.5–13 Hz), beta1 (14–19 Hz), beta2 (19–27 Hz), gamma1 (27– 40 Hz), and gamma2 (41–59 Hz). For the evaluation of significant COH differences between groups Mann–Whitney U-test was used. The accepted level of significance was 99% and 99.9%. The COH analysis showed clearly marked differences between HH and LH participants. The COH between distributed brain regions was considerably higher in HH group within delta, theta1, theta2, alpha1, alpha2 and alpha3 frequency bands as compared to LH group. For example, in theta1 range COH values exceeding 0.5 were revealed for 16% EPs in HH group and for 0.5% EPs in LH, and in alpha1 range — for 50% EPs in HH group and for 29% EPs in LH group. The maximal number of electrode pairs with coherence level significantly higher in the group HH compared to LH one was found within theta1 (142 pairs), theta2 (165 pairs) and alpha3 (131 pairs) frequency ranges. Within high frequency bands higher COH was observed in LH group in comparison with HH one — for 74 electrode pairs in beta2 range and for 70 pairs in gamma1 range. In MH group COH values were intermediate between those of HH and LH groups within the whole frequency range.