Background
Despite recent success in pharmacologic treatment of depression, the inability to
predict individual treatment response remains a liability. This study replicates and
extends findings relating pretreatment electroencephalographic (EEG) alpha to treatment
outcomes for serotonergic medications.
Methods
Resting EEG (eyes-open and eyes-closed) was recorded from a 67-electrode montage in
41 unmedicated depressed patients and 41 healthy control subjects. Patients were tested
before receiving antidepressants including a serotonergic mode of action (selective
serotonin reuptake inhibitor [SSRI], serotonin and norepinephrine reuptake inhibitor,
or SSRI plus norepinephrine and dopamine reuptake inhibitor). EEG was quantified by
frequency principal components analysis of spectra derived from reference-free current
source density (CSD) waveforms, which sharpens and simplifies EEG topographies, disentangles
them from artifact, and yields measures that more closely represent underlying neuronal
current generators.
Results
Patients who did not respond to treatment had significantly less alpha CSD compared
with responders or healthy control subjects, localizable to well-defined posterior
generators. The alpha difference between responders and nonresponders was greater
for eyes-closed than eyes-open conditions and was present across alpha subbands. A
classification criterion based on the median alpha for healthy control subjects showed
good positive predictive value (93.3) and specificity (92.3). There was no evidence
of differential value for predicting response to an SSRI alone or dual treatment targeting
serotonergic plus other monoamine neurotransmitters.
Conclusions
Findings confirm the value of EEG alpha amplitude as a viable predictor of antidepressant
response and suggest that personalized treatments for depression may be identified
using simple electrophysiologic CSD measures.
Key Words
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Article info
Publication history
Published online: April 21, 2011
Accepted:
February 10,
2011
Received in revised form:
February 8,
2011
Received:
November 24,
2010
Identification
Copyright
© 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
