Clinical database development: characterization of EEG phenotypes.
We propose development of evidence-based methods to guide clinical intervention in neurobehavioral syndromes based on categorization of individuals using both behavioral measures and quantification of the EEG (qEEG). Review of a large number of clinical EEG and qEEG studies suggests that it is plausible to identify a limited set of individual profiles that characterize the majority of the population. Statistical analysis has already been used to document "clusters" of qEEG features seen in populations of psychiatric patients. These clusters are considered here as intermediate phenotypes, based on genetics, and are reliable indices of brain function, not isomorphic with DSM categories, and carry implications for therapeutic intervention. We call for statistical analysis methods to be applied to a broad clinical database of individuals diagnosed with neurobehavioral disorders in order to empirically define clusters of individuals who may be responsive to specific neurophysiologically based treatment interventions, namely administration of psychoactive medication and/or EEG neurofeedback. A tentative set of qEEG profiles is proposed based on clinical observation and experience. Implication for intervention with medication and neurofeedback for individuals with these neurophysiological profiles and specific qEEG patterns is presented.
Q-Metrx, Inc., Burbank, California 91506, USA. Jack@q-metrx.com
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Johnstone
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Gunkelman
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Lunt
D016208:Databases, Factual; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D016347:Medical Records Systems, Computerized; D001523:Mental Disorders / Q000145:classification / Q000175:diagnosis*; D009422:Nervous System Diseases / Q000145:classification / Q000175:diagnosis*; D010641:Phenotype; D010818:Practice Patterns, Physicians'; D011379:Prognosis