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Relationships between changes in sustained fronto-striatal connectivity and positive affect in major depression resulting from antidepressant treatment.

ABSTRACT: OBJECTIVE Deficits in positive affect and their neural bases have been associated with major depression. However, whether reductions in positive affect result solely from an overall reduction in nucleus accumbens activity and fronto-striatal connectivity or the additional inability to sustain engagement of this network over time is unknown. The authors sought to determine whether treatment-induced changes in the ability to sustain nucleus accumbens activity and fronto-striatal connectivity during the regulation of positive affect are associated with gains in positive affect. METHOD Using fMRI, the authors assessed the ability to sustain activity in reward-related networks when attempting to increase positive emotion during performance of an emotion regulation paradigm in 21 depressed patients before and after 2 months of antidepressant treatment. Over the same interval, 14 healthy comparison subjects underwent scanning as well. RESULTS After 2 months of treatment, self-reported positive affect increased. The patients who demonstrated the largest increases in sustained nucleus accumbens activity over the 2 months were those who demonstrated the largest increases in positive affect. In addition, the patients who demonstrated the largest increases in sustained fronto-striatal connectivity were also those who demonstrated the largest increases in positive affect when controlling for negative affect. None of these associations were observed in healthy comparison subjects. CONCLUSIONS Treatment-induced change in the sustained engagement of fronto-striatal circuitry tracks the experience of positive emotion in daily life. Studies examining reduced positive affect in a variety of psychiatric disorders might benefit from examining the temporal dynamics of brain activity when attempting to understand changes in daily positive affect.

SUBMITTER: Heller AS

PROVIDER: S-EPMC3563751 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature

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Relationships between changes in sustained fronto-striatal connectivity and positive affect in major depression resulting from antidepressant treatment.

Heller Aaron S AS Johnstone Tom T Light Sharee N SN Peterson Michael J MJ Kolden Gregory G GG Kalin Ned H NH Davidson Richard J RJ

The American journal of psychiatry 20130201 2

OBJECTIVE Deficits in positive affect and their neural bases have been associated with major depression. However, whether reductions in positive affect result solely from an overall reduction in nucleus accumbens activity and fronto-striatal connectivity or the additional inability to sustain engagement of this network over time is unknown. The authors sought to determine whether treatment-induced changes in the ability to sustain nucleus accumbens activity and fronto-striatal connectivity durin ...[more]

PMID: 23223803

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Project description:Background:Electroconvulsive therapy (ECT) is arguably the most effective available treatment for severe depression. Recent studies have used MRI data to predict clinical outcome to ECT and other antidepressant therapies. One challenge facing such studies is selecting from among the many available metrics, which characterize complementary and sometimes non-overlapping aspects of brain function and connectomics. Here, we assessed the ability of aggregated, functional MRI metrics of basal brain activity and connectivity to predict antidepressant response to ECT using machine learning. Methods:A radial support vector machine was trained using arterial spin labeling (ASL) and blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) metrics from n?=?46 (26 female, mean age 42) depressed patients prior to ECT (majority right-unilateral stimulation). Image preprocessing was applied using standard procedures, and metrics included cerebral blood flow in ASL, and regional homogeneity, fractional amplitude of low-frequency modulations, and graph theory metrics (strength, local efficiency, and clustering) in BOLD data. A 5-repeated 5-fold cross-validation procedure with nested feature-selection validated model performance. Linear regressions were applied post hoc to aid interpretation of discriminative features. Results:The range of balanced accuracy in models performing statistically above chance was 58-68%. Here, prediction of non-responders was slightly higher than for responders (maximum performance 74 and 64%, respectively). Several features were consistently selected across cross-validation folds, mostly within frontal and temporal regions. Among these were connectivity strength among: a fronto-parietal network [including left dorsolateral prefrontal cortex (DLPFC)], motor and temporal networks (near ECT electrodes), and/or subgenual anterior cingulate cortex (sgACC). Conclusion:Our data indicate that pattern classification of multimodal fMRI metrics can successfully predict ECT outcome, particularly for individuals who will not respond to treatment. Notably, connectivity with networks highly relevant to ECT and depression were consistently selected as important predictive features. These included the left DLPFC and the sgACC, which are both targets of other neurostimulation therapies for depression, as well as connectivity between motor and right temporal cortices near electrode sites. Future studies that probe additional functional and structural MRI metrics and other patient characteristics may further improve the predictive power of these and similar models.

Dataset Information

Relationships between changes in sustained fronto-striatal connectivity and positive affect in major depression resulting from antidepressant treatment.

Publications

Relationships between changes in sustained fronto-striatal connectivity and positive affect in major depression resulting from antidepressant treatment.

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