Current source density measures of electroencephalographic alpha predict antidepressant treatment response

Craig E Tenke, Jürgen Kayser, Carlye G Manna, Shiva Fekri, Christopher J Kroppmann, Jennifer D Schaller, Daniel M Alschuler, Jonathan W Stewart, Patrick J McGrath, Gerard E Bruder, Craig E Tenke, Jürgen Kayser, Carlye G Manna, Shiva Fekri, Christopher J Kroppmann, Jennifer D Schaller, Daniel M Alschuler, Jonathan W Stewart, Patrick J McGrath, Gerard E Bruder

Abstract

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.

Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1
Figure 1
A. Rotated CSD-fPCA factor loadings waveforms for filtered spectra consisted of low-alpha/theta (black), high-alpha (red), and residual-alpha (green). The rising slope of the low-alpha/theta waveform includes frequencies below 8 Hz (conventional theta band, left of the dotted blue line), while the residual-alpha component includes low-beta. B. Corresponding factor score topographies show that all three alpha factors were greatest at posterior sites, as previously described (Tenke & Kayser, 2005). Low-alpha/theta and high-alpha were greater for eyes-closed, but residual alpha was not. Dots indicate the spherical positions of electrodes (nose at top). Colored lines below maps point to the peak frequencies of corresponding factor loadings on the common abscissa (colors as shown in A).
Figure 2
Figure 2
A. Condition-dependent (eyes-closed minus eyes-open) difference topographies, averaged across high- and low-alpha/theta factors for controls, responders and nonresponders. Alpha reduction was pronounced for nonresponders. B. Corresponding condition-dependent topographies for patients treated with a monotherapy or dual therapy. Both nonresponder groups showed a marked alpha reduction compared to responders.
Figure 3
Figure 3
Scatterplot of mean condition-dependent (eyes-closed minus eyes-open) posterior alpha, averaged across factors for controls, responders and nonresponders. The median for controls (dotted line) was comparable to that for responders (short dashes), but differed markedly from that for nonresponders (long dashes).

Source: PubMed

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