Ian A. Cook

ASSESSING THE ACCURACY OF TOPOGRAPHIC EEG MAPPING FOR DETERMINING LOCAL BRAIN FUNCTION

OBJECTIVE There has been considerable discussion regarding the accuracy of topographic electroencephalographic (EEG) maps for assessing local cerebral function. We performed this study to test the accuracy of EEG mapping by examining the association between electrical activity and the perfusion under each electrode as another measure of local cerebral function. METHODS EEG mapping was performed simultaneously with (H15)2O positron emission tomography (PET) scanning in 6 normal adult subjects, both at rest and during a simple motor task. EEG data were processed using 3 different montages; two EEG power measures (absolute and relative power) were examined. RESULTS Relative power had much stronger associations with perfusion than did absolute power. In addition, calculating power for bipolar electrode pairs and averaging power over electrode pairs sharing a common electrode yielded stronger associations with perfusion than data from referential or single source montages. CONCLUSIONS These findings indicate (1) that topographic EEG mapping can accurately reflect local brain function in a way that is comparable to other methods, and (2) that the choice of EEG measure and montage have a significant influence on the degree with which maps reflect this local activity and function.

Executive dysfunction predicts nonresponse to fluoxetine in major depression.

BACKGROUND Functional brain imaging studies of major depression have consistently revealed hypometabolism or hypoperfusion in specific regions of the prefrontal cortex and basal ganglia. Studies of cognitive functioning in major depression have suggested that some but not all subjects exhibit cognitive deficits that are consistent with frontal-subcortical dysfunction, although the reasons for this heterogeneity are unclear. In this study, we explored this heterogeneity among depressed subjects by examining the relationship between cognitive functioning and treatment outcome. METHOD Subjects with major depression were administered a complete neuropsychological test battery prior to treatment with fluoxetine. RESULTS There were no significant differences between responders and nonresponders to fluoxetine in terms of age, educational achievement, number of past episodes of depression, and estimated premorbid IQ. However, nonresponders performed significantly worse than responders on several pretreatment measures of executive functioning, after controlling for baseline group differences in depression severity. LIMITATIONS The results are based on a small sample of primarily female subjects, resulting in low statistical power and less generalizability to samples of male subjects with depression. CONCLUSIONS The findings suggest that subtle prefrontal dysfunction in subjects with major depression may be predictive of poor response with particular medications. Assessment of the executive functions may play a particular role in pretreatment identification of subjects likely to respond to specific medications.

Yoga as a Complementary Treatment of Depression: Effects of Traits and Moods on Treatment Outcome

Preliminary findings support the potential of yoga as a complementary treatment of depressed patients who are taking anti-depressant medications but who are only in partial remission. The purpose of this article is to present further data on the intervention, focusing on individual differences in psychological, emotional and biological processes affecting treatment outcome. Twenty-seven women and 10 men were enrolled in the study, of whom 17 completed the intervention and pre- and post-intervention assessment data. The intervention consisted of 20 classes led by senior Iyengar yoga teachers, in three courses of 20 yoga classes each. All participants were diagnosed with unipolar major depression in partial remission. Psychological and biological characteristics were assessed pre- and post-intervention, and participants rated their mood states before and after each class. Significant reductions were shown for depression, anger, anxiety, neurotic symptoms and low frequency heart rate variability in the 17 completers. Eleven out of these completers achieved remission levels post-intervention. Participants who remitted differed from the non-remitters at intake on several traits and on physiological measures indicative of a greater capacity for emotional regulation. Moods improved from before to after the yoga classes. Yoga appears to be a promising intervention for depression; it is cost-effective and easy to implement. It produces many beneficial emotional, psychological and biological effects, as supported by observations in this study. The physiological methods are especially useful as they provide objective markers of the processes and effectiveness of treatment. These observations may help guide further clinical application of yoga in depression and other mental health disorders, and future research on the processes and mechanisms.

Regional differences in brain electrical activity in dementia: use of spectral power and spectral ratio measures ☆

The pathologic changes in dementia of the Alzheimers type (DAT) commonly affect selected brain regions. The cortical areas affected in multi-infarct dementia (MID) are less predictable and may be secondary to subcortical gray or white matter damage that is widespread in MID. We compared several types of quantitative EEG power measures (absolute and relative power, and ratios of power) to determine their regional distribution, and their association with changes in cognitive status and age. We examined 49 subjects with clinically diagnosed mild-to-moderate DAT, 29 with mild-to-moderate MID, and 38 elderly controls (CON). We used discriminant analysis to identify, for each parameter type, the brain region and frequency band where the parameter best distinguished between groups of subjects. The parameters showed regional differences in distinguishing between DAT and MID subjects, and in their association with age and cognitive status. All parameters were useful for detecting differences between normal and demented subjects and correctly identified comparable proportions of subjects as having dementia. Subjects who were abnormal on several parameters were much more likely to have dementia. The additive effects of these parameters in correct classification suggest that they may be monitoring different physiologic processes. Combinations of several types of parameters may be more useful than individual parameters for distinguishing demented from non-demented subjects.

Early changes in prefrontal activity characterize clinical responders to antidepressants.

Previous studies have shown that changes in brain function precede clinical response to antidepressant medications. Here we examined quantitative EEG (QEEG) absolute and relative power and a new measure, cordance, for detecting regional changes associated with treatment response. Fifty-one adults with unipolar depression completed treatment trials using either fluoxetine or venlafaxine vs. placebo. Data were recorded at baseline and after 48 h and 1 week on drug or placebo. Baseline and change from baseline values were examined for specific brain regions in four subject groups (medication and placebo responders and nonresponders). No regional baseline QEEG differences were found among the groups; there also were no significant changes in theta power over time. In contrast, medication responders uniquely showed significant decreases in prefrontal cordance at 48 h and 1 week. Clinical differences did not emerge until after four weeks. Subjects with greater changes in cordance had the most complete 8-week responses. These findings implicate the prefrontal region in mediating response to antidepressant medications. Cordance may have clinical applicability as a leading indicator of individual response.

Relationship between brain electrical activity and cortical perfusion in normal subjects

Cerebral glucose uptake and perfusion are accepted as tightly coupled measures of energy utilization in both normal and diseased brain. The coupling of brain electrical activity to perfusion has been demonstrated, however, only in the presence of chronic brain disease. Very few studies have examined the relationship between cerebral electrical activity and energy utilization in normal brain tissue. To clarify this relationship, we performed 33 H2(15)O-positron emission tomography (PET) scans in six normal subjects both at rest and during a simple motor task, and acquired surface-recorded quantitative electroencephalogram (QEEG) data simultaneously with isotope injection. We examined the associations between cerebral perfusion directly underlying each recording electrode and three QEEG measures (absolute power, relative power, and cordance). All EEG measures had moderately strong coupling with perfusion at most frequency bands, although the directions of the associations differed from those previously reported in subjects with stroke or dementia. Of the three QEEG measures examined, cordance had the strongest relationship with perfusion (multiple R2 = 0.58). Cordance and PET were equally effective in detecting lateralized activation associated with the motor task, while EEG power did not detect this activation. Electrodes in the concordant state had a significantly higher mean perfusion than those in the discordant state. These results indicate that normal brain electrical activity has a moderately strong association with cerebral perfusion. Cordance may be the most useful QEEG measure for monitoring cerebral perfusion in subjects without chronic brain disease.

Comparative effectiveness of biomarkers and clinical indicators for predicting outcomes of SSRI treatment in Major Depressive Disorder: results of the BRITE-MD study.

Patients with Major Depressive Disorder (MDD) may not respond to antidepressants for 8 weeks or longer. A biomarker that predicted treatment effectiveness after only 1 week could be clinically useful. We examined a frontal quantitative electroencephalographic (QEEG) biomarker, the Antidepressant Treatment Response (ATR) index, as a predictor of response to escitalopram, and compared ATR with other putative predictors. Three hundred seventy-five subjects meeting DSM-IV criteria for MDD had a baseline QEEG study. After 1 week of treatment with escitalopram, 10 mg, a second QEEG was performed, and the ATR was calculated. Subjects then were randomly assigned to continue with escitalopram, 10 mg, or change to alternative treatments. Seventy-three evaluable subjects received escitalopram for a total of 49days. Response and remission rates were 52.1% and 38.4%, respectively. The ATR predicted both response and remission with 74% accuracy. Neither serum drug levels nor 5HTTLPR and 5HT2a genetic polymorphisms were significant predictors. Responders had larger decreases in Hamilton Depression Rating Scale (Ham-D(17)) scores at day 7 (P=0.005), but remitters did not. Clinician prediction based upon global impression of improvement at day 7 did not predict outcome. Logistic regression showed that the ATR and early Ham-D(17) changes were additive predictors of response, but the ATR was the only significant predictor of remission. Future studies should replicate these results prior to clinical use.

Residual symptoms in depressed outpatients who respond by 50% but do not remit to antidepressant medication.

Little is known about the quantity or quality of residual depressive symptoms in patients with major depressive disorder (MDD) who have responded but not remitted with antidepressant treatment. This report describes the residual symptom domains and individual depressive symptoms in a large representative sample of outpatients with nonpsychotic MDD who responded without remitting after up to 12 weeks of citalopram treatment in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. Response was defined as 50% or greater reduction in baseline 16-item Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR16) by treatment exit, and remission as a final QIDS-SR16 of less than 6. Residual symptom domains and individual symptoms were based on the QIDS-SR16 and classified as either persisting from baseline or emerging during treatment. Most responders who did not remit endorsed approximately 5 residual symptom domains and 6 to 7 residual depressive symptoms. The most common domains were insomnia (94.6%), sad mood (70.8%), and decreased concentration (69.6%). The most common individual symptoms were midnocturnal insomnia (79.0%), sad mood (70.8%), and decreased concentration/decision making (69.6%). The most common treatment-emergent symptoms were midnocturnal insomnia (51.4%) and decreased general interest (40.0%). The most common persistent symptoms were midnocturnal insomnia (81.6%), sad mood (70.8%), and decreased concentration/decision making (70.6%). Suicidal ideation was the least common treatment-emergent symptom (0.7%) and the least common persistent residual symptom (17.1%). These findings suggest that depressed outpatients who respond by 50% without remitting to citalopram treatment have a broad range of residual symptoms. Individualized treatments are warranted to specifically address each patients residual depressive symptoms.

Effectiveness of a quantitative electroencephalographic biomarker for predicting differential response or remission with escitalopram and bupropion in major depressive disorder

We examined the Antidepressant Treatment Response (ATR) index as a predictor of differential response and remission to escitalopram, bupropion, or a combination of the two medications, in subjects with major depressive disorder (MDD). Three hundred seventy-five subjects had a baseline quantitative electroencephalographic (QEEG) study preceding 1 week of treatment with escitalopram, 10 mg, after which a second QEEG was performed and the ATR index was calculated. Subjects then were randomized to continue escitalopram, switch to bupropion, or receive a combination of the two. Clinical response was assessed using the 17-item Hamilton Depression Rating Scale at 49 days of treatment. Accuracy of ATR in predicting response and remission was calculated. There were no significant differences between response and remission rates in the three treatment groups. A single ATR threshold was useful for predicting differential response to either escitalopram or bupropion monotherapy. Subjects with ATR values above the threshold were more than 2.4 times as likely to respond to escitalopram as those with low ATR values (68% vs. 28%). Subjects with ATR values below the threshold who were switched to bupropion treatment were 1.9 times as likely to respond to bupropion alone as those who remained on escitalopram treatment (53% vs. 28%). The ATR index did not provide a useful prediction of response to combination treatment. The ATR index may prove useful in predicting responsiveness to different antidepressant medications.

Biomarkers to Predict Antidepressant Response

During the past several years, we have achieved a deeper understanding of the etiology/pathophysiology of major depressive disorder (MDD). However, this improved understanding has not translated to improved treatment outcome. Treatment often results in symptomatic improvement, but not full recovery. Clinical approaches are largely trial-and-error, and when the first treatment does not result in recovery for the patient, there is little proven scientific basis for choosing the next. One approach to enhancing treatment outcomes in MDD has been the use of standardized sequential treatment algorithms and measurement-based care. Such treatment algorithms stand in contrast to the personalized medicine approach, in which biomarkers would guide decision making. Incorporation of biomarker measurements into treatment algorithms could speed recovery from MDD by shortening or eliminating lengthy and ineffective trials. Recent research results suggest several classes of physiologic biomarkers may be useful for predicting response. These include brain structural or functional findings, as well as genomic, proteomic, and metabolomic measures. Recent data indicate that such measures, at baseline or early in the course of treatment, may constitute useful predictors of treatment outcome. Once such biomarkers are validated, they could form the basis of new paradigms for antidepressant treatment selection.