What is qEEG?
qEEG is an advanced form of electroencephalography (EEG) that quantitatively analyzes the brain’s electrical activity. By placing sensors on the scalp, qEEG measures brainwave patterns and compares them to normative databases. This comparison helps identify deviations associated with specific neurological or psychological conditions.
How does qEEG work?
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Data Collection: Sensors record electrical activity from multiple brain regions while the individual is at rest or performing tasks.
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Signal Processing: The recorded data undergoes mathematical analyses, such as Fourier or wavelet transforms, to quantify the power and frequency of brainwaves.
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Comparison to Norms: The individual’s brainwave patterns are compared to age-matched normative data to identify atypical activity.
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Mapping: Results are visualized as color-coded maps, highlighting areas of overactivity or underactivity.
Why is qEEG important?
qEEG offers a window into the brain’s functional status, providing objective data that can enhance diagnostic accuracy and inform treatment strategies.
qEEG and concussion
Concussions can lead to subtle changes in brain function that are not always detectable through standard imaging. qEEG can identify these changes by revealing alterations in brainwave patterns.
A study published in JAMA Network Open identified five distinct qEEG-based concussion subtypes, suggesting that qEEG can aid in personalized diagnosis and treatment planning for concussion patients.
qEEG and neurological disorders
In individuals with Attention-Deficit/Hyperactivity Disorder (ADHD), qEEG often reveals characteristic patterns, such as increased theta activity and decreased beta activity. Research indicates that qEEG can differentiate ADHD subtypes and may assist in tailoring interventions.
Beyond concussions and ADHD, qEEG has applications in assessing conditions like anxiety disorders, depression, and cognitive impairments. For instance, studies have shown that individuals with Generalized Anxiety Disorder exhibit specific qEEG patterns, such as increased beta activity, which can inform treatment approaches.
Limitations and considerations
While qEEG is a valuable tool, it should be used in conjunction with comprehensive clinical evaluations. It is not a standalone diagnostic method but rather an adjunct that provides additional information to guide clinical decisions.
Conclusion
qEEG brain mapping represents a significant advancement in the assessment of brain function. By providing objective data on neural activity, it enhances our ability to diagnose and manage various neurological conditions. At KOS Integrative Health, we utilize qEEG as part of our commitment to offering personalized, evidence-based care.
References:
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Armañanzas, R., Liang, B., Kanakia, S., Bazarian, J. J., & Prichep, L. S. (2024). Identification of Concussion Subtypes Based on Intrinsic Brain Activity. JAMA Network Open, 7(2), e2355910. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2814991JAMA Network+4National Academies Press+4CiteDrive+4
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Nuwer, M. R., Buchhalter, J., & Shepard, K. M. (2016). Quantitative EEG in attention-deficit/hyperactivity disorder: A companion payment policy review for clinicians and payers. Neurology: Clinical Practice, 6(6), 543–548. https://pubmed.ncbi.nlm.nih.gov/28058208/PubMed
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Kopańska, M., Ochojska, D., Dejnowicz-Velitchkov, A., & Banaś-Ząbczyk, A. (2022). Quantitative Electroencephalography (QEEG) as an Innovative Method in the Diagnosis of Generalized Anxiety Disorders. International Journal of Environmental Research and Public Health, 19(4), 2465. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8879113/Frontiers
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Haneef, Z., Levin, H. S., Frost, J. D., & Mizrahi, E. M. (2013). Electroencephalography and quantitative electroencephalography in mild traumatic brain injury. Journal of Neurotrauma, 30(8), 653–656. https://pubmed.ncbi.nlm.nih.gov/23249295/PubMed
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Kerasidis, H., & Simmons, J. (2021). Quantitative EEG Analysis in Clinical Practice: Concussion Injury. Clinical EEG and Neuroscience, 52(2), 114–118. https://pubmed.ncbi.nlm.nih.gov/33601899/