EEG Spectral Data Distinguishes CFS From Depressed and Healthy Controls

A group at Harvard analyzed spectral data from electroencephalograms (EEGs) performed on 70 Duffy-BMC-Neurology1-206x300CFS patients (1994 criteria), 390 healthy controls, 24 subjects with major depression and 148 patients with prolonged generalized fatigue, a total of 632 subjects. Senior author Anthony Komaroff, M.D., diagnosed the CFS patients. Ten factors were found to distinguish CFS from healthy and depressed controls, with the highest rate of differentiation among unmedicated female CFS patients and female healthy controls, without misclassifying the subjects with major depression as CFS. The model lost some statistical power when applied to subjects taking psychoactive medications; the authors suggest this may reflect a therapeutic effect on the brain function or may modify EEG measurements. ”CFS patients manifest patterns of functional brain coupling that differ from those of normal controls. Such a difference of CFS brain physiology may help explain known differences in cognition, memory, sleep, and affect that afflict CFS patients.” They report that chief among the distinguishing factors were those involved in the brain’s temporal lobe function. (BMC Neurology, July 1, 2011)

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