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March 23, 2020

The use of qEEG for the assessment of depression and for the continued evaluation of antidepressant effects has been explored in several research studies. In this context, use of qEEG technology in patients with depression may assist clinicians in the choice of the appropriate therapeutic strategy, with less of the trial-and-error approach that is usually needed until patients achieve response and remission.

Using QEEG to Diagnose Depression and Monitor Antidepressant Effects

Depression is a potentially life threatening psychiatric disease associated with a wide range of behavioural symptoms and accumulating clinical evidence indicates a link between psychological suffering and electrophysiological anomalies in the brain [1].

Clinical research supports the use of electroencephalography (EEG) in the detection of brain dysfunction in a wide range of psychiatric illnesses including depression [2, 3]. In particular, quantitative EEG (QEEG), the mathematical analysis of the raw EEG waveform using intelligent algorithms [4] is commonly employed in both research labs and neurofeedback clinics [5] for diagnostic purposes and also to monitor treatment response [6, 7]

Sad man holding head with hand
Alpha Frontal Asymmetry

Depression is associated with decreased metabolism in brain circuits that are key for emotion regulation (e.g., amygdala and hippocampus) and data from Q-EEG studies in adults with depression suggest that imbalances in specific EEG frequencies can be linked to both anxiety and depression symptoms.

The recording of QEEG is also employed in youth to estimate the risk for developing mood disorders [8] with subjects who show hypoactivation in the left frontal region of the brain being more at risk of developing depression. 

Another useful measure offered by QEEG is cordance, which is obtained from a combination of absolute power (the amount of activity in a specific EEG frequency at a given electrode) and relative power (the percentage of activity for a frequency band relative to the total frequency spectrum).

Cordance can provide an estimate of antidepressant treatment response or remission with 70% or greater accuracy [9, 10] and quantitative information on white-matter lesions, metabolic changes and perfusion anomalies [11].

The use Q-EEG has also shown diagnostic value in patients with suicide ideation, offering support to self-report scales [12]. For example, individuals with increased risk for suicide as measured by standard psychiatric questionnaires exhibit increased theta (4–8 Hz) and gamma activity (>30 Hz) in both frontal and central brain regions, when compared with low risk subjects [13, 14].

qeeg-depression-patterns

Fig.1 Example of QEEG anomalies in depression

Conclusion

 

The use of QEEG for the assessment of depression and for the continued evaluation of antidepressant effects has been explored in several research studies. In this context, use of QEEG technology in patients with depression may assist clinicians in the choice of the appropriate therapeutic strategy, with less of the trial-and-error approach that is usually needed until patients achieve response and remission.

References

  1. de Aguiar Neto, F.S. and J.L.G. Rosa, Depression biomarkers using non-invasive EEG: A review. Neurosci Biobehav Rev, 2019. 105: p. 83-93.
  2. Dharmadhikari, A.S., et al., Frontal Theta Asymmetry as a Biomarker of Depression. East Asian Arch Psychiatry, 2018. 28(1): p. 17-22.
  3. Verrusio, W., et al., The Mozart Effect: A quantitative EEG study. Conscious Cogn, 2015. 35: p. 150-5.
  4. Jackson, A.F. and D.J. Bolger, The neurophysiological bases of EEG and EEG measurement: a review for the rest of us. Psychophysiology, 2014. 51(11): p. 1061-71.
  5. Soltysik, D., functional-magnetic-resonance-imaging-and quantitative-electroencephalography-fmriqeeg, M. Devices, Editor. 2018, Food and Drug Administration.
  6. Olbrich, S., R. van Dinteren, and M. Arns, Personalized Medicine: Review and Perspectives of Promising Baseline EEG Biomarkers in Major Depressive Disorder and Attention Deficit Hyperactivity Disorder. Neuropsychobiology, 2015. 72(3-4): p. 229-40.
  7. Widge, A.S., et al., Electroencephalographic Biomarkers for Treatment Response Prediction in Major Depressive Illness: A Meta-Analysis. Am J Psychiatry, 2019. 176(1): p. 44-56.
  8. Tomarken, A.J., et al., Resting frontal brain activity: linkages to maternal depression and socio-economic status among adolescents. Biol Psychol, 2004. 67(1-2): p. 77-102.
  9. Hunter, A.M., I.A. Cook, and A.F. Leuchter, The promise of the quantitative electroencephalogram as a predictor of antidepressant treatment outcomes in major depressive disorder. Psychiatr Clin North Am, 2007. 30(1): p. 105-24.
  10. Bares, M., et al., The change of QEEG prefrontal cordance as a response predictor to antidepressive intervention in bipolar depression. A pilot study. J Psychiatr Res, 2012. 46(2): p. 219-25.
  11. Leuchter, A.F., et al., Cordance: a new method for assessment of cerebral perfusion and metabolism using quantitative electroencephalography. Neuroimage, 1994. 1(3): p. 208-19.
  12. Runeson, B., et al., Instruments for the assessment of suicide risk: A systematic review evaluating the certainty of the evidence. PLoS One, 2017. 12(7): p. e0180292.
  13. Arikan, M.K., et al., High-Gamma: A biological marker for suicide attempt in patients with depression. J Affect Disord, 2019. 254: p. 1-6.
  14. Lee, S.M., K.I. Jang, and J.H. Chae, Electroencephalographic Correlates of Suicidal Ideation in the Theta Band. Clin EEG Neurosci, 2017. 48(5): p. 316-321.