Skip to main content

Advertisement

Log in

The EEG Theta/Beta Ratio: A marker of Arousal or Cognitive Processing Capacity?

  • Published:
Applied Psychophysiology and Biofeedback Aims and scope Submit manuscript

Abstract

Attention-Deficit/Hyperactivity Disorder (AD/HD) is the most common psychiatric disorder of childhood and has been extensively researched using EEG technology. Within this literature, one of the most widely examined measures has been the theta/beta ratio. The theta/beta ratio was initially hypothesised to represent the arousal mechanism. However, subsequent research has shown this to be inaccurate and it was hypothesised that the ratio represents cognitive processing capacity. To examine that hypothesis, this study aimed to test the relationship between the P300 and the theta/beta ratio. The P300, absolute alpha and the theta/beta ratio were measured at Fz, Cz and Pz, and correlated in a group of 47 normal adults. A significant positive correlation was found between P300 latency and the theta/beta ratio. No relationship was found between P300 amplitude and the theta/beta ratio. P300 amplitude, but not latency, significantly correlated with alpha power. These results support the hypothesis that the theta/beta ratio is a marker of cognitive processing capacity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Andreassi, J. (2010). Psychophysiology, human behavior and physiological response (5th ed.). New York: Taylor & Francis group.

    Book  Google Scholar 

  • Barry, R., Clarke, A., & Johnstone, S. (2003a). A review of electrophysiology in attention-deficit/hyperactivity disorder: I. Qualitative and quantitative electroencephalography. Clinical Neurophysiology, 114, 171–183.

    Google Scholar 

  • Barry, R., Johnstone, S., & Clarke, A. (2003b). A review of electrophysiology in attention-deficit/hyperactivity disorder: II. Event-related potentials. Clinical Neurophysiology, 114, 184–198.

    Google Scholar 

  • Barry, R., Sokolov, J., E., N (1993). Habituation of phasic and tonic components of the orienting reflex. International Journal of Psychophysiology, 15, 39–42.

    Google Scholar 

  • Barry, R. J., Clarke, A. R., Johnstone, S. J., McCarthy, R., & Selikowitz, M. (2009). Electroencephalogram theta/beta ratio and arousal in AD/HD: evidence of independent processes. Biological Psychiatry, 66, 398–401.

    Article  Google Scholar 

  • Barry, R. J., Clarke, A. R., McCarthy, R., Selikowitz, M., MacDonald, B., & Dupuy, F. E. (2012). Caffeine effects on resting-state electrodermal levels in AD/HD suggest an anomalous arousal mechanism. Biological Psychology, 89, 606–608.

    Article  Google Scholar 

  • Barry, R. J., Clarke, A. R., McCarthy, R., Selikowitz, M., Rushby, J. A., & Ploskova, E. (2004). EEG differences in children as a function of resting-state arousal level. Clinical Neurophysiology, 115, 402–408.

    Google Scholar 

  • Barry, R. J., Kirkaikul, S., & Hodder, D. (2000). EEG alpha activity and the ERP to target stimuli in an auditory oddball paradigm. International Journal of Psychophysiology, 39, 39–50.

    Article  Google Scholar 

  • Barry, R. J., Rushby, J. A., Wallace, M. J., Clarke, A. R., Johnstone, S. J., & Zlojutro, I. (2005). Caffeine effects on resting-state arousal. Clinical Neurophysiology, 116, 2693–2700.

    Google Scholar 

  • Brandt, M. E., Jansen, B. H., & Carbonari, J. P. (1991). Pre-stimulus spectral EEG patterns and the visual evoked response. Electroencephalography and Clinical Neurophysiology, 80, 16–20.

    Google Scholar 

  • Callaway, E., Halliday, R., & Naylor, H. (1983). Hyperactive children’s event-related potentials fail to support underarousal and maturational-lag theories. Archives of General Psychiatry, 40, 1243–1248.

    Article  Google Scholar 

  • Chabot, R. J., & Serfontein, G. (1996). Quantitative electroencephalographic profiles of children with attention deficit disorder. Biological Psychiatry, 40, 951–963.

    Article  Google Scholar 

  • Clarke, A. R., Barry, R. J., Bond, D., McCarthy, R., & Selikowitz, M. (2002a). Effects of stimulant medication on the EEG of children with attention-deficit/hyperactivity disorder. Psychopharmacology (Berl), 164, 277–284.

    Article  Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (1998). EEG analysis in attention-deficit/hyperactivity disorder: a comparative study of two subtypes. Psychiatry Research, 81, 19–29.

    Article  Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (2001a). Age and sex effects in the EEG: Differences in two subtypes of attention-deficit/hyperactivity Disorder. Clinical Neurophysiology, 112, 806–814.

    Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (2001b). EEG-defined subtypes of children with attention-deficit/hyperactivity disorder. Clinical Neurophysiology, 112, 2098–2105.

    Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (2001c). EEG differences in two subtypes of attention-deficit/hyperactivity disorder. Psychophysiology, 38, 212–221.

    Article  Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (2002b). EEG analysis of children with attention-deficit/hyperactivity disorder and comorbid reading disabilities. Journal of Learning Disabilities, 35, 276–285.

    Article  Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (2002c). Children with attention-deficit/hyperactivity disorder and comorbid oppositional defiant disorder: an EEG analysis. Psychiatry Research, 111, 181–190.

    Article  Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., Selikowitz, M., Brown, C., & Croft, R. (2003a). Effects of stimulant medications on the EEG of children with attention-deficit/hyperactivity disorder predominantly inattentive type. International Journal of Psychophysiology, 47, 129–137.

    Article  Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., Selikowitz, M., Clarke, D., & Croft, R. (2003b). EEG in girls with attention-deficit/hyperactivity disorder. Clinical Neurophysiology, 114, 319–328.

    Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., Selikowitz, M., & Croft, R. (2002d). EEG differences between good and poor responders to Methylphenidate in boys with the Inattentive type of ADHD. Clinical Neurophysiology, 113, 1191–1198.

    Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., Selikowitz, M., & Heaven, P. (2011). Childhood EEG as a predictor of adult attention-deficit/hyperactivity disorder. Clinical Neurophysiology, 122, 73–80.

    Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., Selikowitz, M., & Johnstone, S. (2007). Effects of stimulant medications on the EEG of girls with attention-deficit/hyperactivity disorder. Clinical Neurophysiology, 118, 2700–2708.

    Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., Selikowitz, M., & Johnstone, S. (2008). The effects of imipramine hydrochloride on the EEG of children with attention-deficit/hyperactivity disorder. International Journal of Psychophysiology, 67, 35–40.

    Article  Google Scholar 

  • Clarke, A. R., Barry, R. J., McCarthy, R., Selikowitz, M., Magee, C., Johnstone, S., & Croft, R. (2006). The EEG in low IQ children with attention deficit hyperactivity disorder. Clinical Neurophysiology, 117, 1708–1714.

    Article  Google Scholar 

  • De Blasio, F. M., & Barry, R. J. (2013). Prestimulus alpha and beta determinants of ERP responses in the Go/NoGo task. International Journal of Psychophysiology, 89, 9–17.

    Google Scholar 

  • De Blasio, F. M., Barry, R. J., & Steiner, G. Z. (2013). Prestimulus EEG amplitude determinants of ERP responses in a habituation paradigm. International Journal of Psychophysiology, 89, 444–450.

    Google Scholar 

  • Donchin, E. (1981). Surprise!… surprise? Psychophysiology, 18, 493–513.

    Article  Google Scholar 

  • Duncan, C. C., Barry, R. J., Connolly, J. F., Fischer, C., Michie, P. T., Näätänen, R., Polich, J., Reinvang, I., & Van Petten, C. (2009).Event-related potentials in clinical research: Guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clinical Neurophysiology, 120, 1883–1908.

    Article  Google Scholar 

  • Duncan-Johnson, C. C., & Donchin, E. (1977). On quantifying surprise: The variation of event-related potentials with subjective probability. Psychophysiology, 14, 456–467.

    Article  Google Scholar 

  • Dykman, R., Holcomb, P., Oglesby, D., & Ackerman, P. (1982). Electrocortical frequencies in hyperactive, learning-disabled, mixed, and normal children. Biological Psychiatry, 17, 675–685.

    Google Scholar 

  • Egner, T., & Gruzelier, J. H. (2004). EEG biofeedback of low beta band components: Frequency-specific effects on variables of attention and event-related brain potentials. Clinical Neurophysiology, 115, 131–139.

    Google Scholar 

  • Fournier, L. R., Scheffers, M. K., Coles, M. G., Adamson, A., & Abad, E. V. (2000). When complexity helps: An electrophysiological analysis of multiple feature benefits in object perception. Acta Psychologica, 104, 119–142.

    Article  Google Scholar 

  • Hobbs, M. J., Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (2007). EEG abnormalities in adolescent males with AD/HD. Clinical Neurophysiology, 118, 363–371.

    Article  Google Scholar 

  • Intrilligator, J., & Polich, J. (1995). On the relationship between EEG and ERP variability. International Journal of Psychophysiology, 20, 59–74.

    Article  Google Scholar 

  • Janzen, T., Graap, K., Stephanson, S., Marshall, W., & Fitzsimmons, G. (1995). Differences in baseline EEG measures for ADD and normally achieving preadolescent males. Biofeedback and Self-Regulation, 20, 65–82.

    Article  Google Scholar 

  • Jasikutas, P., & Hakerem, G. (1988). The effect of prestimulus alpha activity on P300. Psychophysiology, 25, 157–165.

    Google Scholar 

  • Jasper, H., Solomon, P., & Bradley, C. (1938). Electroencephalographic analyses of behaviour problem children. American Journal of Psychiatry, 95, 641–658.

    Article  Google Scholar 

  • Johnson, R. (1986). A Triarchic Model of P300: For distinguished early career contribution to psychophysiology. Psychophysiology, 23, 367–384.

    Article  Google Scholar 

  • Johnson, R., & Donchin, E. (1978). On how P300 amplitude varies with the utility of the eliciting stimuli. Electroencephalography and Clinical Neurophysiology, 44, 424–437.

    Article  Google Scholar 

  • Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research Reviews, 29, 169–195.

    Article  Google Scholar 

  • Klimesch, W., Sauseng, P., Hanslmayr, S., Gruber, W., & Freunberger, R. (2007). Event-related phase reorganization may explain evoked neural dynamics. Neuroscience and Biobehavioral Reviews, 31, 1003–1016.

    Article  Google Scholar 

  • Kropotov, J. D., Grin-Yatsenko, V. A., Ponomarev, V. A., Chutko, L. S., Yakovenko, E. A., & Nikishena, I. S. (2005). ERPs correlates of EEG relative beta training in ADHD children. International Journal of Psychophysiology, 55, 23–34.

    Article  Google Scholar 

  • Kutas, M., McCarthy, G., & Donchin, E. (1977). Augmenting mental chronometry: The P300 as a measure of stimulus evaluation time. Science, 197, 792–795.

    Article  Google Scholar 

  • Lazzaro, I., Gordon, E., Whitmont, S., Plahn, M., Li, W., Clarke, S., Dosen, A., & Meares, R. (1998). Quantified EEG activity in adolescent attention deficit hyperactivity disorder. Clinical Electroencephalography, 29, 37–42.

    Article  Google Scholar 

  • Lubar, J. (1991). Discourse on the development of EEG diagnostics and biofeedback for attention-deficit/hyperactivity disorders. Biofeedback and Self-regulation, 16, 201–225.

    Google Scholar 

  • Mann, C., Lubar, J. H., Zimmerman, A., Miller, C., & Munchen, R. (1992). Quantitative analysis of EEG in boys with attention deficit hyperactivity disorder: Controlled study with clinical implications. Pediatric Neurology, 8, 30–36.

    Article  Google Scholar 

  • McGarry-Roberts, P. A., Stelmack, R. M., & Campbell, K. B. (1992). Intelligence, reaction time, and event-related potentials. Intelligence, 16, 289–313.

    Article  Google Scholar 

  • Monastra, V., Lubar, J., & Linden, M. (2001). The development of a quantitative electroencephalographic scanning process for attention deficit-hyperactivity disorder: Reliability and validity studies. Neuropsychology, 15, 136–144.

    Article  Google Scholar 

  • Monastra, V., Lubar, J., Linden, M., VanDeusen, P., Green, G., Wing, W., Phillips, A., & Fenger, T. (1999). Assessing attention deficit hyperactivity disorder via quantitative electroencephalography: An initial validation study. Neuropsychology, 13, 424–433.

    Article  Google Scholar 

  • Polich, J. (1997). EEG and ERP assessment of normal aging. Electroencephalography and Clinical Neurophysiology, 104, 244–256.

    Google Scholar 

  • Polich, J. (2007). Updating P300: An integrative theory of P3a and P3b. Clinical Neurophysiology, 118, 2128–2148.

    Article  Google Scholar 

  • Rösler, F., Sutton, S., Johnson, R. Jr., Mulder, G., Fabiani, M., Gorsel, E. P., & Roth, W. T. (1986). Endogenous ERP components and cognitive constructs. A review. Electroencephalography and Clinical Neurophysiology Supplement, 38, 51–92.

    Google Scholar 

  • Satterfield, J., & Dawson, M. (1971). Electrodermal correlates of hyperactivity in children. Psychophysiology, 8, 191–197.

    Article  Google Scholar 

  • Snyder, S. M., Quintana, H., Sexson, S. B., Knott, P., Haque, A. F., & Reynolds, D. A. (2008). Blinded, multi-center validation of EEG and rating scales in identifying ADHD within a clinical sample. Psychiatry Research, 159, 346–358.

    Article  Google Scholar 

  • Snyder, S. M., Rugino, T. A., Hornig, M., & Stein, M. A. (2015). Integration of an EEG biomarker with a clinician’s ADHD evaluation. Brain and Behavior, 5, e00330.

    Article  PubMed  PubMed Central  Google Scholar 

  • Strauß, M., Ulke, C., Paucke, M., Huang, J., Mauche, N., Sander, C., … Hegerl, U. (2018). Brain arousal regulation in adults with attention-deficit/hyperactivity disorder (ADHD). Psychiatry research, 261, 102–108.

    Article  Google Scholar 

  • Wangler, S., Gevensleben, H., Albrecht, B., Studer, P., Rothenberger, A., Moll, G. H., & Heinrich, H. (2011). Neurofeedback in children with ADHD: Specific event-related potential findings of a randomized controlled trial. Clinical Neurophysiology, 122, 942–950.

    Article  Google Scholar 

  • Zhang, D. W., Li, H., Wu, Z., Zhao, Q., Song, Y., Liu, L., … De Blasio, F. M. (2017). Electroencephalogram theta/beta ratio and spectral power correlates of executive functions in children and adolescents with AD/HD. Journal of Attention Disorders, 1087054717718263.

  • Zhang, D. W., Roodenrys, S., Li, H., Barry, R. J., Clarke, A. R., Wu, Z., … Wang, Y. (2017). Atypical interference control in children with AD/HD with elevated theta/beta ratio. Biological Psychology, 128, 82–88.

    Google Scholar 

Download references

Acknowledgements

This research was supported under the Australian Research Council’s Discovery funding scheme (Project Number DP0987232).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Adam R. Clarke.

Ethics declarations

Conflict of interest

There are no conflicts of interest to report.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Clarke, A.R., Barry, R.J., Karamacoska, D. et al. The EEG Theta/Beta Ratio: A marker of Arousal or Cognitive Processing Capacity?. Appl Psychophysiol Biofeedback 44, 123–129 (2019). https://doi.org/10.1007/s10484-018-09428-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10484-018-09428-6

Keywords

Navigation