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Analyzing Brain Patterns with EEG Can Help Predict Effective Use of Medication
Date:7/22/2014

Lawrence, KS (PRWEB) July 22, 2014

Biofeedback – When a behavioral problem such as attention-deficit hyperactivity disorder (ADHD) is diagnosed, selecting medication to best treat it can become a matter of trial and error. Analyzing brain patterns by using electroencephalography (EEG) can help predict which medicine will offer the best result and thus lower the risk of adverse drug events.

The article “Medication Prediction with Electroencephalography Phenotypes and Biomarkers” in the current issue of the journal Biofeedback offers evidence that quantitative EEG assessment can refine the selection of medications by detecting brain patterns. Author Jay Gunkelman uses the example of a 7-year-old child diagnosed with ADHD.

Following current clinical standards, a patient would be diagnosed with ADHD based on behavioral observations as described in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-V). Although this approach defines a problem, it does not predict effective therapy.

Typically, the next step would be to determine which medication would successfully treat the behavior. For ADHD, the options include stimulants, anticonvulsants, antidepressants, and channel blockers—a diverse range of pharmaceutical choices for a single diagnostic cluster. Trying one drug, then another, brings the risk of adverse drug events or severe side effects for the child being treated for ADHD.

The author proposes that quantitative EEG patterns can provide a more reliable basis for medication selection than diagnostic category. Individuals with the same symptom-
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