The Promise of the Quantitative
Electroencephalogram as a Predictor
of Antidepressant Treatment Outcomes
in Major Depressive Disorder
Aimee M. Hunter, PhDa,*, Ian A. Cook, MDb,
Andrew F. Leuchter, MDc
aLaboratory of Brain, Behavior, and Pharmacology, Semel Institute for Neuroscience
and Human Behavior at UCLA, Department of Psychiatry and Biobehavioral Sciences,
David Geffen School of Medicine at UCLA, 760 Westwood Plaza Rm. 37-359,
Los Angeles, CA 90024-1759, USA
bLaboratory of Brain, Behavior, and Pharmacology, Semel Institute for Neuroscience
and Human Behavior at UCLA, Department of Psychiatry and Biobehavioral Sciences,
David Geffen School of Medicine at UCLA, 760 Westwood Plaza Rm. 37-351,
Los Angeles, CA 90024-1759, USA
cLaboratory of Brain, Behavior, and Pharmacology, Semel Institute for Neuroscience
and Human Behavior at UCLA, Department of Psychiatry and Biobehavioral Sciences,
David Geffen School of Medicine at UCLA, 760 Westwood Plaza Rm. 37-452,
Los Angeles, CA 90024-1759, USA
WHY DO WE NEED PREDICTORS OF ANTIDEPRESSANT
A large percentage of patients (30%–53%) fail to respond to an initial course of
antidepressant medication [1–3], and for those who do respond clinical
improvement often takes a long time. Results of the recently completed
multisite study of Sequenced Treatment Alternatives to Relieve Depression,
reviewed extensively by Nierenberg and Fava in this issue, highlight this point.
With 2876 analyzable participants, this landmark study is the single largest
trial of treatment outcomes for depression to date; in contrast to many clinical
trials, minimal exclusionary criteria ensured that participants were representa-
tive of real-world, treatment-seeking outpatients who had nonpsychotic major
depressive disorder. At study outset, all subjects were treated with the
maximum tolerated dose of citalopram (up to 60 mg) for up to 14 weeks.
Even with aggressive dosing, this representative selective serotonin reuptake
This work was supported by grant R01-MH069217 and contract N01 MH90003/GMO-010111 from the
National Institute of Mental Health (IAC), grant R01 AT 002479 from the National Center for
Complementary and Alternative Medicine (AFL), and a grant from Aspect Medical Systems (IAC).
*Corresponding author. E-mail address: email@example.com (A.M. Hunter).
0193-953X/07/$ – see front matter
ª 2007 Elsevier Inc. All rights reserved.
Psychiatr Clin N Am 30 (2007) 105–124
OF NORTH AMERICA
inhibitor (SSRI) showed only modest effectiveness. Examining a response
criterion of a reduction of 50% or more on the 16-item Quick Inventory of
Depressive Symptomatology, Self-Report (QIDS-SR) and a remission criterion
of five or lower on the QIDS-SR, only 47% of subjects responded and 29%
remitted. Moreover, even for subjects who responded and/or remitted after
14 weeks of treatment, symptomatic improvement was slow. After 6 weeks,
only about two thirds (65.2%) of ultimate responders had responded, and
just over half (52.9%) of ultimate remitters had remitted . These data
mirror the typical experience in clinical practice; that is, response or remission
to a given medication is uncertain, and it takes a long time to determine
The inability to predict a patient’s response to a particular treatment can
lead to a delay in effective treatment, which in turn can have a number of
deleterious consequences. Without any reliable means of predicting outcome,
patients and physicians are left to use a trial-and-error strategy in which the
trial often lasts 6 to 12 weeks. Patients who do not respond to an initial treat-
ment must endure subsequent trials to determine the effectiveness of different
regimens, and many abandon treatment while still symptomatic . The most
apparent consequence of delayed effective treatment is that patients continue
to suffer from the symptoms of depression including increased risk for suicide
. There also is evidence that prolonged depression is associated with delete-
rious effects on the central nervous system. Major depression has been associ-
ated with reduced hippocampal volume , and longer durations of untreated
depressive episodes have been associated with lower hippocampal volume .
Patients who do not respond to their first antidepressant trial are at increased
risk for never receiving adequate treatment , and delays in effective
treatment are associated with a poorer prognosis for the course of illness
over subsequent episodes. A longer index episode (>12 weeks) has been
associated with a 37% lower rate of recovery in subsequent episodes .
One study examining the impact of 16 sociodemographic and clinical factors
identified rapid remission as the most important predictor of favorable long-
term outcome . In addition to health concerns, medical expenditures also
increase with increasing numbers of ineffective treatment trials. A study of
7737 depressed subjects found higher inpatient, outpatient, and pharmaceuti-
cal health care costs with increasing numbers of changes in antidepressant
treatment regimen . The introduction of reliable predictors of response
to treatment thus could potentially shorten the course of treatment and
improve long-term treatment outcomes in depression.
CLINICAL AND PHYSIOLOGIC PREDICTORS
OF ANTIDEPRESSANT RESPONSE
The clinical relevance of predicting response has driven a great deal of
exploration of possible sociodemographic, clinical, and pretreatment physio-
logic predictors [11–16]. Many inconsistencies exist across studies, however,
and most factors that seem to have heuristic value in differentiating groups
106HUNTER, COOK, & LEUCHTER
of responders or nonresponders have not proven to be reliable pretreatment
predictors of response for individual patients [17–21]. As yet, none has proven
sufficiently useful to be adopted into clinical practice for predicting treatment
response [14–22]. A few notable measurements have begun to demonstrate
increased levels of reliability and accuracy as predictors of antidepressant
response. For example, considerable data in the burgeoning literature on
pharmacogenetics have linked response to SSRI treatment with genetic
variants in the sequences coding for specific molecules including the serotonin
(5-HT) transporter, 5-HT-2A-receptor, tryptophan hydroxylase, brain-derived
neurotrophic factor, G protein beta3 subunit, interleukin-1beta, and angioten-
sin-converting enzyme, but with inconsistencies among results . Further
work with large patient samples stratified for intervening variables is needed
before drawing more definite conclusions . Although there is hope is
that the identification of key genetic components eventually will facilitate
individualized treatment planning (so-called ‘‘personalized medicine’’), small
variances of analyzed polymorphisms may diminish optimism for immediate
application at the clinical level . In a line of work examining functional
brain asymmetry, perceptual asymmetry as assessed using dichotic listening
tests has been demonstrated repeatedly as a predictor of response to fluoxetine
with some evidence of clinically meaningful accuracy; however, gender-
dependent relationships between predictor and outcome variables require
further study [26–28]. Also, it is unknown whether this marker is medication
Other investigations have examined changes in physiologic function during
antidepressant treatment as biomarkers of therapeutic response. Several
studies using positron emission tomography (PET) to assess cerebral metabo-
lism during treatment have reported differences in prefrontal and/or cingulate
activity between responders and nonresponders to antidepressant medications.
Most studies report that metabolism increases in ventral paralimbic areas or in
the caudate nucleus during effective antidepressant treatment ; cortical
metabolism, however, has been reported either to increase or decrease, de-
pending upon the study [30,31]. Most studies of cerebral blood flow, as well
as most recent studies of cerebral metabolism, indicate that a decrease in
cerebral perfusion in dorsolateral prefrontal cortex is associated with effective
antidepressant treatment. In reports of a relatively large sample of subjects
who had depression, investigators found decreases in perfusion in prefrontal
cortex [32,33]. Previous findings also have reported decreases in prefrontal
cerebral perfusion in subjects responding to various antidepressant medica-
tions . Other investigators have reported decreases in prefrontal cortex
metabolism in subjects responding to paroxetine treatment [35,36]. Despite
these encouraging findings, the real-world clinical application of PET scans
for predicting treatment outcomes may be limited. Dosimetry concerns
impose limitations on the safe use of radioactive tracers for serial scanning.
This technology also is costly and invasive, and access is limited outside
a research setting.
107PROMISE OF QUANTITATIVE EEG
OF ANTIDEPRESSANT OUTCOMES
Electroencephalography (EEG) has long held appeal as an easily accessible
technique to measure central nervous system activity. Since Hans Berger’s
first recording of the human EEG in the mid-1920s and early demonstra-
tions that drugs that influence human behavior also produce obvious effects
on human EEG, numerous attempts have been made to apply the recording
of electrical activity from scalp electrodes to a wide range of psychiatric con-
cerns including diagnosis, treatment selection, and drug development. His-
torically, the field has covered a broad range of applications and
methodologies. Researchers have examined various spontaneous and activa-
tion-induced EEG features measured at different time-points, recorded using
a variety of electrode montages, and analyzed using different approaches.
Moreover, few early studies controlled for potentially confounding variables.
Although the lack of standardization makes comparisons among early find-
ings difficult, and the absence of controls leaves open the interpretation of
results, these early reports provide the first evidence of the potential capabil-
ity of quantitative electroencephalography (QEEG) measurements to predict
clinical outcome to antidepressant medications. More recently, studies have
begun to refine methods to give EEG markers greater predictive capability
and to standardize those methods to allow replication of results. In addition,
some newer studies have used more rigorous experimental designs and con-
trols, thus allowing greater certainty in interpretations of the observed rela-
tionships between EEG markers and clinical response during treatment with
Rationale Behind Electroencephalographic Markers of Response
A potential EEG predictor of antidepressant response can be measured (1)
before treatment (ie, as a baseline or pretreatment measure), (2) shortly after
start of drug, or (3) as a ‘‘change variable’’ or ‘‘change indicator’’ describing
change in the EEG from a pretreatment baseline to a time-point after initiating
treatment. In any case, to have clinical utility as a predictor, the EEG measure
of course must precede the clinical response. The assumption underlying
a baseline EEG indicator is that state and/or trait factors reflected in the
EEG are related to how the subject will respond to antidepressant medication.
The assumptions behind an EEG predictor measured sometime early after the
onset of drug treatment are that (1) antidepressant medication produces
changes in the EEG soon after beginning treatment, and (2) identifiable
medication-related EEG changes are reliably linked to later clinical changes.
A subject’s brain state or change in brain state after a brief period of antide-
pressant treatment presumably reflects the interaction between patient factors
and exposure to medication and would be a leading indicator of eventual
108HUNTER, COOK, & LEUCHTER
Early Work Suggesting Relationships Among Electroencephalographic
Findings, Symptoms of Depression, and Antidepressant Medication
A considerable body of research supports the assertion that antidepressant
medication effects are physiologically detectable in the EEG. Prior work in
the ‘‘pharmaco-EEG’’ tradition has shown that administration of antidepres-
sant compounds to healthy subjects produces reliable EEG changes within
hours of dosing [37–47]. Although there are reproducible EEG effects of
antidepressant medications across subjects, variances in the EEG response
also have been noted . Differences in medication effects on the EEG
have been linked to individual differences in the pre-exposure EEG ,
suggesting that the baseline EEG may indeed capture state or trait aspects of
central nervous system function that moderate subsequent effects of medication
on the central nervous system.
Use of the EEG to predict antidepressant outcome has roots in an early
study that examined pretreatment EEG and the change from pre- to post-
treatment EEG as potential predictors of outcome to amitriptyline and pirlin-
dole . Responder versus nonresponder groups assessed after 4 weeks of
treatment were differentiated on the basis of both their pretreatment baseline
EEGs and pre- to posttreatment EEG changes after 4 weeks. Responder groups
were distinguished by a number of EEG parameters, especially in the alpha
range. Among other features, responders were characterized by left later-
alization of baseline alpha power, decreases in absolute alpha power, and
increases in slower frequencies over 4 weeks. Although EEGs were recorded
from occipital, central, and frontal regions, only occipital regions were evalu-
ated in the primary report. Later reanalyses of these data examined the
topographical distribution of alpha activity across recording regions and found
lateralized differences in anterior as well as posterior regions between
responders and nonresponders [50,51]. Some EEG correlates of response
were medication specific [50,51], whereas others were observed with both
A later study examining EEG predictors of 3-week response to the heterocy-
clic antidepressants clomipramine and maprotiline found that early changes in
the EEG (ie, changes from baseline to 2 hours after the first daily drug infusion)
distinguished between later responders and nonresponders to either medication
. In that study, the EEG measure used as a predictor measure was the
frequency of non-A epochs (ie, 2-second epochs that do not represent alpha
activity) as calculated using a novel procedure to quantify spatiotemporal
changes in alpha activity .
Lateralized baseline alpha power was associated with response to fluoxetine
in a study of 53 depressed adults . Left dominant pretreatment values of
alpha power (indicative of greater right hemisphere activation) were associated
with 12-week response as measured using the Clinical Global Impression
Improvement scale. This predictive relationship was evident for women but
not for men.
109PROMISE OF QUANTITATIVE EEG
Pretreatment baseline and postdrug change differences in theta-band log
transformed relative power were found to distinguish responders from
nonresponders to 4 weeks of open-label treatment with the tricyclic antidepres-
sant imipramine . At pretreatment, responders exhibited significantly less
overall theta power; pretreatment differences in other frequencies were not
significant. Acute (3 hours after initial dose) postdrug change in overall theta
power distinguished responders from nonresponders. Considering EEG
changes over the first 2 weeks of treatment, responders showed significantly
greater increments in anterior theta power than did nonresponders.
In a study examining baseline EEG predictors of response to the SSRI agent
paroxetine, lower baseline relative theta power again was associated with greater
improvement . Of note, all significant pretreatment indicators were localized
reported a positive association between overall lower baseline theta power and
response . Differences in these findings could be related to different
mechanisms of action between tricyclic and SSRI medications.
Taken together, these reports provide evidence suggesting that pre- and
posttreatment EEG measurements (especially measurements in alpha and theta
bands and potentially lateralized and frontal measurements) are related to later
clinical outcome of antidepressant treatment. These reports show subtle but
statistically significant EEG differences between groups of responders and
nonresponders; however, the considerable overlap in the distribution of values
for responders and nonresponders limits the predictive validity for individual
patients. Another consideration regarding these studies is that none examined
placebo-control conditions; therefore, a limit of these investigations is that it is
not possible to discern whether the EEG findings were related generally to
clinical improvement or more specifically to drug efficacy (specific versus
nonspecific or placebolike effects).
Quantitative Electroencephalographic Biomarkers: a New Wave
of Accuracy in Predicting Antidepressant Response
Neurobiologic conceptual model underlying relationships between frontal theta
measurements (relative power and cordance) and antidepressant response
Several lines of reasoning support the rationale for examining frontal EEG
measurements in the theta band (4–8 Hz) in relation to antidepressant medi-
cation effects and changes in depressive symptoms. The underlying neuro-
biologic conceptual model draws on prior work indicating that (1) activity in
anterior cingulate and dorsolateral prefrontal regions is related both to dep-
ression and changes in mood in response to treatment; (2) prefrontal theta
activity is associated with other measurements of cortical activity in the anterior
cingulate and seems to be related to network processing of affective infor-
mation; and (3) the effects of antidepressant medication produce alterations
in theta band activity.
A consistent finding in neuroimaging studies from independent research
groups is that of abnormal metabolism or perfusion in the dorsolateral
110HUNTER, COOK, & LEUCHTER
prefrontal cortex and/or the anterior cingulate cortex in depressed subjects
[29,30,36,56–62]. Prefrontal and cingulate regions also figure consistently and
prominently in studies using EEG to examine brain function associated with
depressed mood [27,63–69], and these regions also have been examined using
functional MRI [70,71]. Networks of projecting white-matter fibers connect
these regions, both neuroanatomically and functionally [72–76]. The impor-
tance of these anatomic tracts in this context is that rhythmic theta activity
recorded at the scalp in prefrontal channels may reflect both the intrinsic activ-
ity originating in the dorsolateral prefrontal cortex and the projected rhythms
that are generated in deep locations (eg, the anterior cingulate) and influence
activity in the cortex nearer to the recording electrodes.
Theta band activity in particular has been examined with regard to coordi-
nated activity between the midline prefrontal and cingulate regions. Studies
that combined surface EEG recordings and magnetoencephalographic
(MEG) data have indicated that surface theta rhythms recorded from prefron-
tal channels are correlated with deep theta MEG activity in the anterior cingu-
late [77,78]. Activity in the theta band seems to be important to the integration
of activity across distributed neural networks [79,80]. Shifts in theta band
activity also have been particularly linked with processing emotionally related
stimuli and meditation-related changes in emotional state [81–84].
Antidepressant compounds [54,55,85–88] and treatment with electroconvul-
sive therapy  have been shown to alter theta activity. Pretreatment theta
cordance measured from electrodes overlying the cingulate cortex has been
related to the response to electroconvulsive therapy in major depressive disor-
der (MDD) . Using EEG tomography, pretreatment theta activity
associated with antidepressant response has been localized to the anterior
Theta band relative power
Several naturalistic studies using open-label, flexible-dose SSRI treatment have
demonstrated the predictive capability of theta band relative power measured
from frontal electrodes. In a cohort of 36 adult outpatients meeting criteria for
MDD, frontal theta band relative power 1 week after start of drug was signifi-
cantly lower in responders than in nonresponders . Response was defined
as a reduction of 50% or more in scores on the 17-item Hamilton Depression
Rating Scale (HamD17) from baseline to week eight. Lower theta band relative
power at 1 week also correlated with percent improvement in the HamD17score
over 8 weeks. Importantly, this measure predicted response with 83% overall
accuracy (76% sensitivity, 93% specificity) and .88 area under the receiver oper-
ating curve. This essential finding was replicated by the same group of investiga-
tors in a larger sample of 68 patients who had MDD treated with SSRIs .
Again, frontal theta band relative power 1 week after start of drug was signifi-
cantly lower in responders than in nonresponders and was negatively correlated
with the magnitude of clinical improvement. The predictor yielded an overall
accuracy of 67% with 71% sensitivity and 61% specificity.
111PROMISE OF QUANTITATIVE EEG
Another analysis of frontal theta band relative power, also from the same
investigators, examined 52 subjects who had MDD grouped by depressive
subtype (melancholic, atypical, or typical)  and treated naturalistically.
Baseline frontal theta band relative power was significantly lower in SSRI
responders than in nonresponders, and the difference in frontal theta band
relative power between responders and nonresponders was similar across
clinical subtypes. Baseline theta band relative power alone predicted response
with 71% accuracy (72% sensitivity, 70% specificity) and in combination
with measurements of theta band relative power at 1 week resulted in
improved prediction (79% accuracy, 84% sensitivity, and 70% specificity.)
Here, the addition of the week one measure added to the ability to correctly
An independent study of 22 outpatients who had MDD examined frontal
theta band relative power measurements as predictors of 8-week response to
citalopram . Mean decreases in frontal theta band relative power were
observed in responders but not in nonresponders at weeks one, two, and
four. The decrease in theta band relative power 2 weeks after start of medi-
cation was significantly greater in treatment responders than in nonresponders,
and decreases predicted response with 73% accuracy (73% sensitivity, 73%
These studies are comparable in many respects. Each used identical, auto-
mated EEG recording methods to measure frontal theta band relative power,
examined outpatients who had MDD receiving open-label treatment with
SSRIs, and assessed response/nonresponse outcome as an improvement of
50% or more on the HamD17scale after 8 weeks of treatment. Each of these
studies demonstrated significant associations between clinical response to
antidepressant medication and lower frontal theta band activity or decreases
in frontal theta band activity within the first 2 weeks after start of medication.
Strong predictive capability was demonstrated for frontal theta band relative
power biomarkers, but there was some variability in the EEG time-points
used as predictors in these studies of theta band relative power. Predictive
capability was shown either for baseline, week one, or change at week two
EEG measurements, depending on the study; therefore they cannot be viewed
as direct replications of the same finding. Furthermore, because these studies
did not examine control subjects treated with placebo, the capacity of these
indicators to discriminate between specific response to medication and
nonspecific effects is unknown.
Quantitative electroencephalographic cordance development
Cordance is a measure that combines absolute and relative power with the
goal of extracting information with greater physiologic meaning from
QEEG. Absolute power, the amount of power in a frequency band at a given
electrode (measured in lV2), and relative power, the percentage of power
contained in a frequency band relative to the total power across the entire
spectrum, are associated inconsistently with direct measurements of cerebral
112HUNTER, COOK, & LEUCHTER
energy use, making their physiologic significance unclear . For example,
relationships between EEG power measurements and perfusion or metabo-
lism show considerable variability across frequency bands and sites [96,97],
with some studies showing only weak associations . Absolute power
and relative power are, in fact, complementary measurements of brain activ-
ity  that have independent associations with perfusion . Cordance
combines traditional absolute power and relative power measurements to
achieve a stronger association with cerebral perfusion than is seen with either
measure alone. A detailed description of how cordance is calculated is pro-
vided elsewhere .
Several studies have demonstrated relationships between QEEG cordance
and other physiologic measurements. In a series of outpatient case studies,
cordance was reported to have strong associations with other measurements
of brain structure and function including white-matter lesions detected on
MRI, metabolism measured by PET using fluorodeoxyglucose, and perfusion
measured by hexamethylpropyleneamine oxime single-photon emission
computed tomography (SPECT) . A larger study examining 27 outpatients
who had degenerative or vascular dementia showed that cordance had
a stronger association with perfusion (measured using SPECT) than either
absolute or relative power measurements alone, and this relationship held
across multiple brain regions as evidenced by data from frontal, temporal,
and occipital electrode sites . Finally, a study of normal healthy subjects
compared associations between perfusion (measured using O15PET) and
QEEG measurements including absolute power, relative power, and cordance
. Of the three EEG measurements examined, cordance was found to have
a moderately strong association with perfusion and was the strongest of the
measurements examined, both during a resting state and motor task perfor-
mance. In addition, cordance was as effective as PET in detecting lateralized
activation associated with a motor task; EEG power measurements did not
detect this activation.
Theta cordance as a predictor of antidepressant treatment outcomes. The first systematic
report to indicate that theta cordance might be sensitive to pharmacotherapy
interventions was made in the context of a study that used cordance to assess
cerebral energy use in late-life depression . QEEG theta cordance
measurements were obtained for 27 depressed subjects and 27 matched con-
trols with the hypothesis that depressed subjects would show overall alterations
consistent with the decreases in perfusion and metabolism seen using PET 
or SPECT . Results supported the hypothesis and demonstrated differ-
ences in global and regional cordance between depressed and control subjects.
It is important for response prediction that cordance patterns were found to
differ significantly between depressed subjects who were being treated with
antidepressant medication and those who were not. This observation, albeit
cross-sectional, suggested that theta cordance might be sensitive to changes
in brain function attributable to antidepressant treatment.
113PROMISE OF QUANTITATIVE EEG
The relationship between theta cordance and treatment response was
explored in a series of individual cases that illustrated frontal decreases in theta
cordance as early as 48 hours after beginning medication preceding clinical
improvement in depressed outpatients receiving open-label treatment with
SSRI or serotonin-norepinephrine reuptake inhibitor (SNRI) medications
. Later, a larger case series prospectively examined decreases in prefrontal
cordance as a predictor of 2-month outcome in seven subjects who had major
depression receiving naturalistic open-label treatment with SSRI or SNRI anti-
depressants . Subjects were free of psychotropic medications for 2 weeks
before enrollment in the study. All four responders showed large decreases in
cordance 48 hours and 1 week after initiating medication. None of the three
nonresponders showed this pattern; one showed only a slight decrease, and
the other two nonresponders showed frank increases in prefrontal theta
band cordance. Using a simple dichotomous decrease/no decrease predictor
(in which decrease predicted response), change in prefrontal theta band
cordance yielded an overall accuracy of 86%, with 100% sensitivity and 67%
Data from individual cases prompted the first hypothesis-driven placebo-con-
trolled study of theta band cordance as a potential biomarker of antidepressant
response . Decreases in prefrontal theta band cordance at 48 hours and at
1 week after start of medication were hypothesized to predict 8-week antide-
pressant response (final HamD17? 10). Data were pooled from 51 depressed
patients across two placebo-controlled studies that used fluoxetine or venlafax-
ine, respectively, as the active medication. There was a trend finding at 48
hours, and at 1week change in prefrontal theta band cordance significantly dis-
tinguished medication responders from all other groups (medication nonre-
sponders, placebo responders, and placebo nonresponders). In addition, the
degree of change in prefrontal cordance was significantly associated with
degree of response. Using prefrontal cordance decrease/no decrease as a dichot-
omous predictor of response accurately classified 9 of 13 medication
responders (69%) and 9 or 12 medication nonresponders (75%) for an overall
accuracy of 72%. Decreases in prefrontal theta band cordance did not predict
response among subjects assigned randomly to placebo. In fact, a separate
study of the same 51 subjects revealed a distinctly different pattern of change
(4- and 8-week increases in prefrontal cordance) for placebo responders as
compared with all other groups .
The finding of early decrease in prefrontal cordance as a predictor of
response has been replicated by the same group of investigators and by an
independent research team. In a study of patients who had treatment-resistant
depression, prefrontal theta band cordance EEG measurements were obtained
a cohort of 12 outpatients at baseline and approximately 1 week after beginning
a new treatment . These patients had not responded to monotherapy and
were beginning a new treatment as prescribed by their treating psychiatrists. In
contrast to earlier studies that had used a drug-free interval or drug washout
period before obtaining the baseline EEG [104,105], these treatment-resistant
114HUNTER, COOK, & LEUCHTER
subjects were evaluated without a drug-free interval between trials. Response
was evaluated after 8 to 10 weeks. Of six responders, five showed an early
decrease in cordance; only two of the six nonresponders showed an early
cordance decrease. The predictor yielded accurate classification for 75% of
the subjects. Findings using cordance have been replicated independently in
a study of 17 depressed inpatients receiving open-label treatment with antide-
pressants from a variety of classifications . Prefrontal theta band cordance
decreases after 1 week predicted response (>50% reduction of Montgomery-
Asberg Depression Rating Scale scores after 4 weeks of treatment) with an
overall accuracy of 88% (100% sensitivity, 83% specificity). In a pooled analysis
of 54 subjects from three studies across investigative teams, decreases in
prefrontal cordance yielded an overall accuracy of 78% .
Across studies of MDD subjects treated with various antidepressant medi-
cations, decreases in prefrontal theta band cordance 1 week after start of
medication have predicted response consistently with overall accuracy ranging
from 72% to 88%. Examination of this predictor in randomized, double-blind,
placebo-controlled trials has demonstrated specificity for this marker as an
indicator of medication efficacy.
Future Directions Using Spontaneous Electroencephalographic
Measurements to Predict Other Antidepressant Outcomes
Recent evidence suggests that EEG measurements might be useful in predicting
other positive outcomes as well as negative outcomes of antidepressant treat-
ment (ie, treatment-emergent adverse events. Although most studies to date
examining QEEG predictors of clinical outcome have focused on treatment
response (typically ? 50% improvement in symptoms or a final HamD17score
? 10), there is growing emphasis on remission (eg, final Ham-D score ? 7 or
? 5) as the endpoint goal of treatment. Although prefrontal channels seem to
predict response with a high degree of accuracy, recent evidence suggests that
electrodes overlying the midline and right frontal region may predict remission
[110,111]. With regard to treatment-emergent adverse events, a promising new
line of work suggests that EEG markers also may be able to predict worsening
of somatic and mood symptoms. EEG markers have been linked to the overall
occurrence of common side effects including headache, nausea, and sexual dys-
function  and to the emergence of increased thoughts of suicide  re-
ported during antidepressant treatment.
OTHER ELECTROENCEPHALOGRAPHIC-RELATED PREDICTORS
OF ANTIDEPRESSANT OUTCOMES
Loudness Dependence of Auditory Evoked Potentials
In addition to measurements of spontaneous EEG activity, such as relative
power and cordance, measurements of brain response to a stimulus have
been examined as predictors of treatment response. A variety of preclinical
and clinical studies have suggested that the loudness dependence of auditory
evoked potentials (LDAEP) may reflect activity in the brain’s serotonergic
115PROMISE OF QUANTITATIVE EEG
system. These auditory evoked potentials arise from activity in the primary
auditory cortex and can be studied using dipole source analysis ; the ratio
of N1/P2 amplitude values increases with increasing tone loudness during
auditory stimulation, and LDAEP values are inversely related to central
serotonergic activity. Patients who had a strong LDAEP (a marker of a low
serotonergic state) before treatment responded significantly better to SSRI med-
ications than did patients who had a lower LDAEP (and, presumably, high or
normal serotonergic activity) [114–119]. One study has examined the predic-
tive value of the LDAEP in relation to treatment with the SNRI reboxetine.
In contrast to the direction of amplitude changes associated with SSRI
response, lower pretreatment intensity-dependent N1 amplitude slopes were
significantly associated with reboxetine response, suggesting that LDAEP
differentially predicts clinical response to serotonergic versus noradrenergic
antidepressant psychopharmacotherapy . As with the approaches de-
scribed previously in this article, the LDAEP method shows promise in
differentiating between patients who may or may not respond to a particular
medication; further independent replication under controlled conditions will
help clarify how it might best be used for guiding treatment decisions in clinical
Nonlinear Measurements of Brain Physiology
EEG power and cordance are both linear measurements of the EEG power
spectrum. A nonlinear measure of EEG activity, the bispectrum, also
has been examined for use in detecting pretreatment differences between re-
sponders and nonresponders to antidepressant treatment. The bispectrum
quantifies phase and power coupling between EEG components  and
could offer a complementary measurement of regional brain activity. In an
investigation of adult outpatients treated with fluoxetine, venlafaxine, or pla-
cebo , bispectrum values were calculated for frequency triples of the
form [f1, f2, f1þf2] at 1 Hz resolution using a single frontotemporal channel
(T3-Fp1). Across all treatment groups, the bispectrum in the range [12 Hz <
f1 < 24 Hz, f2 < 6 Hz] was higher in the more severely depressed patients,
with a significant correlation between HamD17score and bispectrum value.
Additionally, there were baseline differences between responders and nonre-
sponders to medication. Further replications and extensions of that work are
underway, and bispectrum-based measurements might be combined with
cordance or other linear measurements to create a composite biomarker with
improved predictive accuracy.
HOW MIGHT INFORMATION FROM
ELECTROENCEPHALOGRAPHIC PREDICTORS BE USED
IN CLINICAL PRACTICE?
Reliable prediction of antidepressant treatment outcomes would have benefit
regardless of whether indicators for a given antidepressant regimen point
toward response or failure for a patient. Pretreatment, as compared with
116HUNTER, COOK, & LEUCHTER
postdrug, indicators might be interpreted slightly differently. The value of
a positive EEG change indicator would be to provide the patient and physician
with some degree of assurance that continued treatment will be fruitful and to
avoid unnecessary (and perhaps ineffective) switching and/or augmentation of
medications. Increased confidence in a positive outcome also could encourage
treatment adherence even as patients contend with side effects that can peak
before therapeutic effects are realized. In the case of a negative change indica-
tor, the probably ineffective treatment regimen could be changed far sooner
than is current common practice, and the new regimen could be initiated
shortly thereafter. Evidence from a study of subjects who had stage I treat-
ment-resistant depression suggests that the predictive capability of QEEG cord-
ance biomarkers does not require a drug-free interval between treatments .
Positive baseline indicators could suggest that a given individual is generally
suitable for antidepressant medication whether because of state or trait factors;
pretreatment EEG biomarkers (LDAEPs notwithstanding) have not been stud-
ied extensively with respect to their ability to predict differential response to
different medications. The value of a negative baseline indicator for antidepres-
sant response is unknown, although it is possible that other types of interven-
tions would be more effective for individuals who have a poor prognostic
indicator for pharmacotherapy. Another interpretation is that a negative base-
line indicator suggests that the transient state of the individual is not conducive
to antidepressant response at that time. In this view, medication-free measure-
ments repeated over time might change from an unfavorable to a favorable
indicator for pharmacotherapy, thus identifying a particular time during which
initiation of antidepressant treatment would likely lead to clinical response or
CAVEATS AND CAUTIONS
The comparatively low cost, high patient acceptability, and technological ease
of performing QEEG data collection and analysis can be viewed as strengths of
this approach. On the other hand, these same attributes mean that there is
a low barrier to entry in the field, and individuals and groups with little training
or experience can gather QEEG data on patients or research subjects. The
reliability and interpretability of these data may be inconsistent or worse.
The conclusions that can be drawn from any innovative clinical research
study need to be subjected to scientific scrutiny through peer review and inde-
pendent replication of findings before they can be considered for use in advanc-
ing clinical care, whether the innovation is a new molecule designed for
therapeutic use or a technology proposed for guiding treatment. Unfortunately,
the low barriers to entry in the QEEG arena have meant that naively designed,
poorly executed, or inappropriately analyzed data are not subjected consis-
tently to the normal checks and balances of the scientific method, and systems
purporting to diagnose and/or provide guidance for care are available without
having been subjected to rigorous review expected of other advances in
biomedical research. The research and clinical communities therefore must
117PROMISE OF QUANTITATIVE EEG
be attuned to the reality that not all ‘‘QEEG’’ systems represent the same
measure or technique. Only through thoughtful consideration of each method
separately can the claims advanced for a particular technique be assessed. After
this type of careful review, methods for which there is an adequate evidence
base enter the mainstream of care.
Recent studies have shown overall accuracy rates of 72% to 88% using baseline
and/or 1-week change in QEEG biomarkers to predict clinical outcome to
treatment with various antidepressant medications. In some cases, findings
have been replicated across academic institutions and have been studied in
the context of randomized, placebo-controlled trials. Recent EEG findings
are corroborated by studies that use techniques with greater spatial resolution
(eg, PET, MEG) in localizing brain regions pertinent to clinical response. As
such, EEG measurements increasingly are validated by other physiologic
measurements that have the ability to assess deeper brain structures. Contin-
ued progress along these lines may lead to the realized promise of QEEG
biomarkers as predictors of antidepressant treatment outcome in routine
clinical practice. In the larger context, use of QEEG technology to predict
antidepressant response in major depression may mean that more patients
will achieve response and remission with less of the trial-and-error approach
that currently accompanies antidepressant treatment.
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