3 EEG Spectral Analysis
51
to relieve the necessity of multiple-testing correction by decreasing the number of
simultaneous comparisons. Likewise, the basic frequency bands (delta, theta, alpha,
beta, and gamma) can also be divided into multiple subbands. Alpha and beta bands
are sometimes fragmented by (1) the low-alpha and high-alpha and (2) the low-beta
and high-beta subbands, to investigate the functions of more specific bands [1, 39].
References
1. L.I. Aftanas, S.A. Golocheikine, Human anterior and frontal midline theta and lower alpha
reflect emotionally positive state and internalized attention: high-resolution EEG investigation
of meditation. Neurosci. Lett. 310, 57–60 (2001). https://doi.org/10.1016/S0304-3940(01)020
94-8
2. American Clinical Neurophysiology, Guideline fourteen: guidelines for recording clinical EEG
on digital media. J. Clin. Neurophysiol. 11, 114–115 (1994)
3. American Clinical Neurophysiology, Guideline twelve: guidelines for long-term monitoring
for epilepsy. J. Clin. Neurophysiol. 11, 88–110 (1994)
4. J.S. Barlow, The Electroencephalogram: Its Patterns and Origins (MIT Press, Cambridge,
1993), pp. 213–220
5. R.J. Barry, A.R. Clarke, S.J. Johnstone, A review of electrophysiology in attentiondeficit/hyperactivity disorder: I. Qual. Quant. Electroencephalogr. Clin. Neurophysiol. 114,
171–183 (2003). https://doi.org/10.1016/S1388-2457(02)00362-0
6. H. Berger, Über das Elektrenkephalogramm des Menschen. Archiv für Psychiatrie und Nervenkrankheiten 87, 527–570 (1929). https://doi.org/10.1007/bf01797193
7. M.A. Brazier, Preliminary proposal for an EEG terminology by the Terminology Committee
of the International Federation for Electroencephalography and Clinical Neurophysiology.
Electroencephalogr. Clin. Neurophysiol. 13, 646–650 (1961)
8. T.H. Budzynski, H.K. Budzynski, J.R. Evans, A. Abarbanel, Introduction to Quantitative EEG
and Neurofeedback: Advanced Theory and Applications (Elsevier, 2009)
9. J. Carrier, S. Land, D.J. Buysse, D.J. Kupfer, T.H. Monk, The effects of age and gender on sleep
EEG power spectral density in the middle years of life (ages 20–60 years old). Psychophysiology 38, 232–242 (2001). https://doi.org/10.1111/1469-8986.3820232
10. J.W. Cooley, J.W. Tukey, An algorithm for the machine calculation of complex Fourier series.
Math. Comput. 19, 297–301 (1965). https://doi.org/10.2307/2003354
11. J. Dien, Issues in the application of the average reference: review, critiques, and recommendations. Behav. Res. Methods Instrum. Comput. 30, 34–43 (1998). https://doi.org/10.3758/bf03
209414
12. G. Dietsch, Fourier-analyse von Elektrencephalogrammen des Menschen Pflüger’s Archiv für
die gesamte. Physiologie des Menschen und der Tiere 230, 106–112 (1932). https://doi.org/1
0.1007/bf01751972
13. P. Djuric, S. Kay, Spectrum Estimation and Modeling, in The Digital Signal Processing Hanbook, 2nd edn., ed. by V. Madisetti (CRC Press, Boca Raton, 2017)
14. R.E. Dustman, D.E. Shearer, R.Y. Emmerson, Life-span changes in EEG spectral amplitude,
amplitude variability and mean frequency. Clin. Neurophysiol. 110, 1399–1409 (1999). https://
doi.org/10.1016/S1388-2457(99)00102-9
15. I. Feinberg, R.L. Koresko, N. Heller, EEG sleep patterns as a function of normal and pathological aging in man. J. Psychiatr. Res. 5, 107–144 (1967). https://doi.org/10.1016/0022-3956
(67)90027-1
16. I.H. Gotlib, EEG alpha asymmetry, depression, and cognitive functioning. Cogn. Emot. 12,
449–478 (1998). https://doi.org/10.1080/026999398379673
51
to relieve the necessity of multiple-testing correction by decreasing the number of
simultaneous comparisons. Likewise, the basic frequency bands (delta, theta, alpha,
beta, and gamma) can also be divided into multiple subbands. Alpha and beta bands
are sometimes fragmented by (1) the low-alpha and high-alpha and (2) the low-beta
and high-beta subbands, to investigate the functions of more specific bands [1, 39].
References
1. L.I. Aftanas, S.A. Golocheikine, Human anterior and frontal midline theta and lower alpha
reflect emotionally positive state and internalized attention: high-resolution EEG investigation
of meditation. Neurosci. Lett. 310, 57–60 (2001). https://doi.org/10.1016/S0304-3940(01)020
94-8
2. American Clinical Neurophysiology, Guideline fourteen: guidelines for recording clinical EEG
on digital media. J. Clin. Neurophysiol. 11, 114–115 (1994)
3. American Clinical Neurophysiology, Guideline twelve: guidelines for long-term monitoring
for epilepsy. J. Clin. Neurophysiol. 11, 88–110 (1994)
4. J.S. Barlow, The Electroencephalogram: Its Patterns and Origins (MIT Press, Cambridge,
1993), pp. 213–220
5. R.J. Barry, A.R. Clarke, S.J. Johnstone, A review of electrophysiology in attentiondeficit/hyperactivity disorder: I. Qual. Quant. Electroencephalogr. Clin. Neurophysiol. 114,
171–183 (2003). https://doi.org/10.1016/S1388-2457(02)00362-0
6. H. Berger, Über das Elektrenkephalogramm des Menschen. Archiv für Psychiatrie und Nervenkrankheiten 87, 527–570 (1929). https://doi.org/10.1007/bf01797193
7. M.A. Brazier, Preliminary proposal for an EEG terminology by the Terminology Committee
of the International Federation for Electroencephalography and Clinical Neurophysiology.
Electroencephalogr. Clin. Neurophysiol. 13, 646–650 (1961)
8. T.H. Budzynski, H.K. Budzynski, J.R. Evans, A. Abarbanel, Introduction to Quantitative EEG
and Neurofeedback: Advanced Theory and Applications (Elsevier, 2009)
9. J. Carrier, S. Land, D.J. Buysse, D.J. Kupfer, T.H. Monk, The effects of age and gender on sleep
EEG power spectral density in the middle years of life (ages 20–60 years old). Psychophysiology 38, 232–242 (2001). https://doi.org/10.1111/1469-8986.3820232
10. J.W. Cooley, J.W. Tukey, An algorithm for the machine calculation of complex Fourier series.
Math. Comput. 19, 297–301 (1965). https://doi.org/10.2307/2003354
11. J. Dien, Issues in the application of the average reference: review, critiques, and recommendations. Behav. Res. Methods Instrum. Comput. 30, 34–43 (1998). https://doi.org/10.3758/bf03
209414
12. G. Dietsch, Fourier-analyse von Elektrencephalogrammen des Menschen Pflüger’s Archiv für
die gesamte. Physiologie des Menschen und der Tiere 230, 106–112 (1932). https://doi.org/1
0.1007/bf01751972
13. P. Djuric, S. Kay, Spectrum Estimation and Modeling, in The Digital Signal Processing Hanbook, 2nd edn., ed. by V. Madisetti (CRC Press, Boca Raton, 2017)
14. R.E. Dustman, D.E. Shearer, R.Y. Emmerson, Life-span changes in EEG spectral amplitude,
amplitude variability and mean frequency. Clin. Neurophysiol. 110, 1399–1409 (1999). https://
doi.org/10.1016/S1388-2457(99)00102-9
15. I. Feinberg, R.L. Koresko, N. Heller, EEG sleep patterns as a function of normal and pathological aging in man. J. Psychiatr. Res. 5, 107–144 (1967). https://doi.org/10.1016/0022-3956
(67)90027-1
16. I.H. Gotlib, EEG alpha asymmetry, depression, and cognitive functioning. Cogn. Emot. 12,
449–478 (1998). https://doi.org/10.1080/026999398379673