Anxious depression is associated with poorer acute outcomes than nonanxious depression following antidepressant treatment.

These findings suggest that "effective" placebo treatment induces changes in brain function that are distinct from those associated with antidepressant medication. If these results are confirmed, cordance may be useful for differentiating between medication and placebo responders.

No abstract

This paper uses a general latent variable framework to study a series of models for non-ignorable missingness due to dropout. Non-ignorable missing data modeling acknowledges that missingness may depend on not only covariates and observed outcomes at previous time points as with the standard missing at random (MAR) assumption, but also on latent variables such as values that would have been observed (missing outcomes), developmental trends (growth factors), and qualitatively different types of development (latent trajectory classes). These alternative predictors of missing data can be explored in a general latent variable framework using the Mplus program. A flexible new model uses an extended pattern-mixture approach where missingness is a function of latent dropout classes in combination with growth mixture modeling using latent trajectory classes. A new selection model allows not only an influence of the outcomes on missingness, but allows this influence to vary across latent trajectory classes. Recommendations are given for choosing models. The missing data models are applied to longitudinal data from STAR*D, the largest antidepressant clinical trial in the U.S. to date. Despite the importance of this trial, STAR*D growth model analyses using non-ignorable missing data techniques have not been explored until now. The STAR*D data are shown to feature distinct trajectory classes, including a low class corresponding to substantial improvement in depression, a minority class with a Ushaped curve corresponding to transient improvement, and a high class corresponding to no improvement. The analyses provide a new way to assess drug efficiency in the presence of dropout.

Previous studies have shown that changes in brain functionClinicians long have observed a lag time of several weeks between the initiation of antidepressant treatment and clinical response for many patients (Hyman and Nestler 1996;Katz et al. 1996). Some individuals do have early symptomatic improvement, and this has been reported to predict further improvement over the next several weeks (Nierenberg et al. 1995). Reports have suggested that some physiologic changes are seen shortly after initiation of treatment (Sulser 1989;Beck 1995;Dahmen et al. 1997). No clinically practical physiologic predictor of treatment response has yet been identified with these techniques, however, and the relationship of early physiologic changes to eventual clinical outcome remains incompletely understood.Quantitative electroencephalography (QEEG) has been used as a physiologic measure in efforts to address these questions. Prior work with "pharmaco-EEG" techniques has shown that the administration of antidepressant compounds yields reproducible changes in EEG activity in healthy control subjects within a few hours of dosing (Saletu et al. 1982(Saletu et al. , 1983(Saletu et al. , 1986(Saletu et al. , 1987(Saletu et al. , 1987 Grunberger 1985, 1988;Sannita et al. 1983;Sannita 1990; Early Prefrontal Changes in Depression 121Itil et al. 1984;Herrmann et al. 1991;Luthringer et al. 1996). The relationship of these immediate EEG changes in control subjects to eventual clinical response in a depressed population is unclear. Other QEEG work with depressed subjects has found that changes from baseline in theta power early in the course of treatment may characterize groups of depressed patients who are more likely to respond to antidepressant treatment (Ulrich et al. 1994). Unfortunately, the overlap in the value of these changes between responder and nonresponder groups precluded the use of this measure in response prediction for individual subjects, and prior research did not indicate how to relate changes in theta power to other measures of regional brain activity (e.g., regional cerebral blood flow or metabolism). We previously have shown that absolute and relative power are complementary measures of brain activity (Leuchter et al. 1993). A relatively new QEEG measure, "cordance," combines information from both absolute and relative power measures (Leuchter et al. 1994a(Leuchter et al. , 1994b. The algorithm yields two indicators: a categorical value ("concordant" or "discordant" state) and a numerical value for each electrode. In an earlier report with the categorical measure , we observed that depressed subjects exhibiting the concordant state prior to treatment had better treatment outcomes when treated with fluoxetine than did subjects with the discordant state. In this report, we use the num*erical values of cordance, because they allow examination of changes in regional brain activity with treatment. In validation against data collected simultaneously with [H 2 15O]-positron emission tomography (PET), cordance values in the the...

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.

Clinical and neuropathological evaluation of elderly subjects with dementia has traditionally concentrated upon the focal distribution of brain disease, ignoring changes in the complex connections that link brain areas and that are crucial for cognition. We examined subjects with the two most common forms of dementia in the elderly (dementia of the Alzheimer type or DAT, and multi-infarct dementia or MID); and used electroencephalographic (EEG) coherence to examine the effects of these illnesses on the functional connections between brain areas. We studied coherence between brain areas known to be linked by two different types of connections: (i) dense narrow bands of long corticocortical fibres; (ii) broad complex networks of corticocortical and corticosubcortical fibres. Areas that were linked by dense narrow bands of long corticocortical fibres showed greatly diminished coherence in subjects with DAT; among MID subjects, this coherence was not significantly affected. Areas that were linked by broad connective networks showed the largest decreases in coherence among MID subjects. These findings are consistent with neuropathological evidence that Alzheimer's disease is a neocortical 'disconnection syndrome' in which there is a loss of structural and functional integrity of long corticocortical tracts. The findings further suggest that the vascular disease of MID most prominently affects broad fibre networks that may be more vulnerable to diffuse subcortical vascular damage. A ratio of coherence from complex corticocortical-corticosubcortical networks divided by coherence from long corticocortical tracts correctly classified 76% of subjects into DAT and MID categories. Overall, these results indicate that EEG coherence detects basic pathophysiological differences between subjects with DAT and MID, and that these differences may be clinically useful.

Symptoms of Major Depressive Disorder (MDD) are hypothesized to arise from dysfunction in brain networks linking the limbic system and cortical regions. Alterations in brain functional cortical connectivity in resting-state networks have been detected with functional imaging techniques, but neurophysiologic connectivity measures have not been systematically examined. We used weighted network analysis to examine resting state functional connectivity as measured by quantitative electroencephalographic (qEEG) coherence in 121 unmedicated subjects with MDD and 37 healthy controls. Subjects with MDD had significantly higher overall coherence as compared to controls in the delta (0.5–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), and beta (12–20 Hz) frequency bands. The frontopolar region contained the greatest number of “hub nodes” (surface recording locations) with high connectivity. MDD subjects expressed higher theta and alpha coherence primarily in longer distance connections between frontopolar and temporal or parietooccipital regions, and higher beta coherence primarily in connections within and between electrodes overlying the dorsolateral prefrontal cortical (DLPFC) or temporal regions. Nearest centroid analysis indicated that MDD subjects were best characterized by six alpha band connections primarily involving the prefrontal region. The present findings indicate a loss of selectivity in resting functional connectivity in MDD. The overall greater coherence observed in depressed subjects establishes a new context for the interpretation of previous studies showing differences in frontal alpha power and synchrony between subjects with MDD and normal controls. These results can inform the development of qEEG state and trait biomarkers for MDD.