Neuro Metrics and How They Help You


Neurofeedback and neurotherapy are emerging fields in mental health that use technology to monitor and train the brain’s electrical activity. These methods can help identify EEG-based neuro biomarkers, which can be used to help therapists better understand their patients and tailor their treatment plans to individual needs.

EEG-based neuro biomarkers are electrical patterns that can be found by looking at an individuals brainwaves. These biomarkers can provide valuable insights into a patient’s brain function, which can  then inform treatment plans and help therapists identify areas of focus for interventions.

Here are a few examples of how EEG-based neuro biomarkers can help therapists better work with their patients:

  1. Elevated frontal theta power: Elevated theta power in the frontal regions of the brain has been consistently observed in individuals with anxiety disorders. By identifying this biomarker in a patient’s EEG, a therapist can target these regions of the brain with neurofeedback and neurotherapy interventions to reduce anxiety symptoms.
  2. Decreased alpha power: Decreased alpha power in the frontal and posterior regions of the brain has been associated with higher levels of anxiety, particularly in individuals with generalized anxiety disorder. By identifying this biomarker in a patient’s EEG, a therapist can target these regions of the brain with neurofeedback and neurotherapy interventions to increase alpha power and reduce anxiety symptoms. 
  3. Increased theta/beta ratio: An increased theta/beta power ratio has been found to be associated with ADHD, particularly in the frontal regions of the brain. By identifying this biomarker in a patient’s EEG, a therapist can target these regions of the brain with neurofeedback and neurotherapy interventions to reduce ADHD symptoms.
  4. By incorporating EEG-based neuro biomarkers into their practice, therapists can better understand their patients’ individual neuro profiles and tailor their interventions to address specific areas of concern. This personalized approach can lead to more effective and efficient outcomes, and ultimately, improved mental health for their patients.

    Divergence has created an easy and fast way to help you obtain a variety of these relevant neuro biomarkers in a single assessment called TheraQ. This rapid neuro assessment can be completed in under 5 minutes and can even be deployed in a fully remote scenario. This means you can move from assessment to protocol selection to a training all inside a single session while still having time left to address important clinical concerns. This solution offers a compelling advantage over most other assessments which typically require 30 to 40 minutes to complete and often require messy pastes and gels.

    To learn more about how TheraQ works, visit the TheraQ product page.


  1. Angelakis, E., Lubar, J. F., & Stathopoulou, S. (2004). Electroencephalographic peak alpha frequency correlates of cognitive traits. Neuroscience Letters, 371(1), 60-63.
  2. Jokić-Begić, N., & Begić, D. (2003). Quantitative electroencephalogram (qEEG) in combat veterans with post-traumatic stress disorder (PTSD). Nordic journal of psychiatry, 57(5), 351-355.
  3. Başar, E. (2012). A review of gamma, theta and alpha brain oscillations in cognitive processes and in cognitive impairment. International Journal of Psychophysiology, 86(1), 1-7.
  4. Mathewson, K. J., Jetha, M. K., Drmic, I. E., Bryson, S. E., Goldberg, J. O., Hall, G. B., … & Schmidt, L. A. (2010). Autonomic predictors of Stroop performance in young and middle-aged adults. International Journal of Psychophysiology, 76(3), 123-129.
  5. Putman, P. (2011). Resting state EEG delta–beta coherence in relation to anxiety, behavioral inhibition, and selective attentional processing of threatening stimuli. International Journal of Psychophysiology, 80(1), 63-68.
  6. Başar, E., Başar-Eroğlu, C., Karakaş, S., & Schürmann, M. (2001). Gamma, alpha, delta, and theta oscillations govern cognitive processes. International Journal of Psychophysiology, 39(2-3), 241-248.
  7. Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Research Reviews, 29(2-3), 169-195.
  8. Teixeira, S., Machado, S., Paes, F., Velasques, B., Silva, J. G., Sanfim, A., … & Budde, H. (2014). Time-dependent effects of cardiovascular exercise on memory. Exercise and sport sciences reviews, 42(2), 79-89.
  9. Arns, M., Conners, C. K., & Kraemer, H. C. (2013). A decade of EEG Theta/Beta Ratio Research in ADHD: a meta-analysis. Journal of attention disorders, 17(5), 374-383.
  10. Barry, R. J., Clarke, A. R., & Johnstone, S. J. (2003). A review of electrophysiology in attention-deficit/hyperactivity disorder: I. Qualitative and quantitative electroencephalography. Clinical Neurophysiology, 114(2), 171-183.
  11. Lansbergen, M. M., Arns, M., Van Dongen-Boomsma, M., Spronk, D., & Buitelaar, J. K. (2011). The increase in theta/beta ratio on resting-state EEG in boys with attention-deficit/hyperactivity disorder is mediated by slow alpha peak frequency. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 35(1), 47-52.
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