EEG Correlates of Trait and Mathematical Anxiety during Lexical and Numerical Error-Recognition Tasks
EEG correlates of mathematical and trait anxiety level
were studied in 52 healthy Russian-speakers during execution of
error-recognition tasks with lexical, arithmetic and algebraic
conditions. Event-related spectral perturbations were used as a
measure of brain activity. The ERSP plots revealed alpha/beta
desynchronizations within a 500-3000 ms interval after task onset
and slow-wave synchronization within an interval of 150-350 ms.
Amplitudes of these intervals reflected the accuracy of error
recognition, and were differently associated with the three conditions.
The correlates of anxiety were found in theta (4-8 Hz) and beta2 (16-
20 Hz) frequency bands. In theta band the effects of mathematical
anxiety were stronger expressed in lexical, than in arithmetic and
algebraic condition. The mathematical anxiety effects in theta band
were associated with differences between anterior and posterior
cortical areas, whereas the effects of trait anxiety were associated
with inter-hemispherical differences. In beta1 and beta2 bands effects
of trait and mathematical anxiety were directed oppositely. The trait
anxiety was associated with increase of amplitude of
desynchronization, whereas the mathematical anxiety was associated
with decrease of this amplitude. The effect of mathematical anxiety
in beta2 band was insignificant for lexical condition but was the
strongest in algebraic condition. EEG correlates of anxiety in theta
band could be interpreted as indexes of task emotionality, whereas
the reaction in beta2 band is related to tension of intellectual
resources.
[1] M. H. Ashcraft, M.H. (2002). Math anxiety: Personal, educational, and
cognitive consequences. Directions in Psychological Science, 2002, vol.
11, pp. 181-185.
[2] C. D. Spielberger, C.D. Trait-state anxiety and motor behavior. Journal
of Motor Behavior, 1971, vol. 3, pp. 265-279.
[3] J. A. Gray, & N. McNaughton, N. (2000). The neuropsychology of
anxiety (2nd ed). Oxford University Press, 2000. p. 443.
[4] M. W. Eysenck, N. Derakshan, R. Santos, M. G. Calvo Anxiety and
cognitive performance: attentional control theory. Emotion, 2007. vol. 7.
N 2. pp. 336–356.
[5] M. H. Ashcraft, J. A. Krause Working memory, math performance, and
math anxiety, Psychon Bull Rev, 2007, vol. 14, № 2, pp. 243-248.
[6] A. N. Savostyanov, A. C. Tsai, A. Yu. Zhigalov, E. A. Levin, J. D. Lee
and M. Liou Trait Anxiety and Neurophysiology of Executive Control in
the Stop-Signal Paradigm, in Trait Anxiety, Edited by Anna S. Morales.
- New York: Nova Science Publishers, 2011. – pp. 191-222.
[7] Y. L. Khanin Short management to application of Ch.D. Spilberger's
scale of reactive and personal anxiety /Y. L. Khanin. - L, 1976. - 198 p.
American Psychiatry Association. Diagnostic and statistical Manual of
Mental Disorders.
[8] L. Alexander, & C. Martray The development of an abbreviated version
of the Mathematics Anxiety Rating Scale, Measurement and Evaluation
in Counseling and Development, 1989. – vol. 22, № 3, pp. 143–150.
[9] A. Delorme, S. Makeig EEGLAB: an open source toolbox for analysis of
single-trial EEG dynamics including independent component analysis, J.
Neurosci. Methods, 2004, vol. 134, № 1, pp. 9–21.
[10] S. Makeig, A. J. Bell, T. P. Jung, T. J. Sejnowski Independent
component analysis of electroencephalografic data Adv. Neural Inf.
Process. Syst., 1996, vol. 8, pp. 145–151.
[11] W. Klimesch, EEG alpha and theta oscillations reflect cognitive and
memory performance: a review and analysis, Brain Research Reviews,
1999, vol. 29, № 2-3, pp. 169-195.
[12] L. I. Aftanas, A. A. Varlamov, S. V. Pavlov, V. P. Makhnev and N. V.
Reva, Affective picture processing: event-related synchronization within
individually defined human theta band is modulated by valence
dimension, Neuroscience Letters, 2001, vol. 303, № 2, pp. 115-118.
[13] R. Adolphs, Neural systems for recognizing emotion, Current Opinion in
Neurobiology, 2002, vol. 12, № 2, pp. 169-177.
[14] L. X. Blonder, D. Bowers and K. M. Heilman, The Role of the Right-
Hemisphere in Emotional Communication, Brain, 1999, vol. 114, pp.
1115-1127.
[15] E. Basar (Ed.), Brain Functions and Oscillations. II. Integrative Brain
Function. Neurophysiology and Cognitive Processes, Springer, Berlin,
Heidelberg, 1999.
[1] M. H. Ashcraft, M.H. (2002). Math anxiety: Personal, educational, and
cognitive consequences. Directions in Psychological Science, 2002, vol.
11, pp. 181-185.
[2] C. D. Spielberger, C.D. Trait-state anxiety and motor behavior. Journal
of Motor Behavior, 1971, vol. 3, pp. 265-279.
[3] J. A. Gray, & N. McNaughton, N. (2000). The neuropsychology of
anxiety (2nd ed). Oxford University Press, 2000. p. 443.
[4] M. W. Eysenck, N. Derakshan, R. Santos, M. G. Calvo Anxiety and
cognitive performance: attentional control theory. Emotion, 2007. vol. 7.
N 2. pp. 336–356.
[5] M. H. Ashcraft, J. A. Krause Working memory, math performance, and
math anxiety, Psychon Bull Rev, 2007, vol. 14, № 2, pp. 243-248.
[6] A. N. Savostyanov, A. C. Tsai, A. Yu. Zhigalov, E. A. Levin, J. D. Lee
and M. Liou Trait Anxiety and Neurophysiology of Executive Control in
the Stop-Signal Paradigm, in Trait Anxiety, Edited by Anna S. Morales.
- New York: Nova Science Publishers, 2011. – pp. 191-222.
[7] Y. L. Khanin Short management to application of Ch.D. Spilberger's
scale of reactive and personal anxiety /Y. L. Khanin. - L, 1976. - 198 p.
American Psychiatry Association. Diagnostic and statistical Manual of
Mental Disorders.
[8] L. Alexander, & C. Martray The development of an abbreviated version
of the Mathematics Anxiety Rating Scale, Measurement and Evaluation
in Counseling and Development, 1989. – vol. 22, № 3, pp. 143–150.
[9] A. Delorme, S. Makeig EEGLAB: an open source toolbox for analysis of
single-trial EEG dynamics including independent component analysis, J.
Neurosci. Methods, 2004, vol. 134, № 1, pp. 9–21.
[10] S. Makeig, A. J. Bell, T. P. Jung, T. J. Sejnowski Independent
component analysis of electroencephalografic data Adv. Neural Inf.
Process. Syst., 1996, vol. 8, pp. 145–151.
[11] W. Klimesch, EEG alpha and theta oscillations reflect cognitive and
memory performance: a review and analysis, Brain Research Reviews,
1999, vol. 29, № 2-3, pp. 169-195.
[12] L. I. Aftanas, A. A. Varlamov, S. V. Pavlov, V. P. Makhnev and N. V.
Reva, Affective picture processing: event-related synchronization within
individually defined human theta band is modulated by valence
dimension, Neuroscience Letters, 2001, vol. 303, № 2, pp. 115-118.
[13] R. Adolphs, Neural systems for recognizing emotion, Current Opinion in
Neurobiology, 2002, vol. 12, № 2, pp. 169-177.
[14] L. X. Blonder, D. Bowers and K. M. Heilman, The Role of the Right-
Hemisphere in Emotional Communication, Brain, 1999, vol. 114, pp.
1115-1127.
[15] E. Basar (Ed.), Brain Functions and Oscillations. II. Integrative Brain
Function. Neurophysiology and Cognitive Processes, Springer, Berlin,
Heidelberg, 1999.
@article{"International Journal of Medical, Medicine and Health Sciences:70539", author = "Alexander N. Savostyanov and Tatiana A. Dolgorukova and Elena A. Esipenko and Mikhail S. Zaleshin and Margherita Malanchini and Anna V. Budakova and Alexander E. Saprygin and Tatiana A. Golovko and Yulia V. Kovas", title = "EEG Correlates of Trait and Mathematical Anxiety during Lexical and Numerical Error-Recognition Tasks", abstract = "EEG correlates of mathematical and trait anxiety level
were studied in 52 healthy Russian-speakers during execution of
error-recognition tasks with lexical, arithmetic and algebraic
conditions. Event-related spectral perturbations were used as a
measure of brain activity. The ERSP plots revealed alpha/beta
desynchronizations within a 500-3000 ms interval after task onset
and slow-wave synchronization within an interval of 150-350 ms.
Amplitudes of these intervals reflected the accuracy of error
recognition, and were differently associated with the three conditions.
The correlates of anxiety were found in theta (4-8 Hz) and beta2 (16-
20 Hz) frequency bands. In theta band the effects of mathematical
anxiety were stronger expressed in lexical, than in arithmetic and
algebraic condition. The mathematical anxiety effects in theta band
were associated with differences between anterior and posterior
cortical areas, whereas the effects of trait anxiety were associated
with inter-hemispherical differences. In beta1 and beta2 bands effects
of trait and mathematical anxiety were directed oppositely. The trait
anxiety was associated with increase of amplitude of
desynchronization, whereas the mathematical anxiety was associated
with decrease of this amplitude. The effect of mathematical anxiety
in beta2 band was insignificant for lexical condition but was the
strongest in algebraic condition. EEG correlates of anxiety in theta
band could be interpreted as indexes of task emotionality, whereas
the reaction in beta2 band is related to tension of intellectual
resources.", keywords = "EEG, brain activity, lexical and numerical error-recognition
tasks, mathematical and trait anxiety.", volume = "9", number = "7", pages = "554-5", }