Brain Imaging Correlates of Depressive Symptom Severity and Predictors of Symptom Improvement After Antidepressant Treatment

Brain Mapping Unit, University of Cambridge, Department of Psychiatry, Addenbrooke's Hospital, Cambridge, UK.
Biological Psychiatry (Impact Factor: 10.26). 10/2007; 62(5):407-14. DOI: 10.1016/j.biopsych.2006.09.018
Source: PubMed


It would be therapeutically useful to predict clinical response to antidepressant drugs. We evaluated structural magnetic resonance imaging (MRI) and functional MRI (fMRI) data as predictors of symptom change in people with depression.
Brain structure and function were measured with MRI in 17 patients with major depression immediately before 8 weeks treatment with fluoxetine 20 mg/day. For fMRI, patients were scanned during visual presentation of faces representing different intensities of sadness. Clinical response was measured by change in serial scores on the Hamilton Rating Scale for Depression. Symptom change scores (and baseline symptom severity) were regressed on structural and functional MRI data to map brain regions where grey matter volume, or activation by sad facial affect processing, was significantly associated with symptom change (or baseline severity).
Faster rates of symptom improvement were strongly associated with greater grey matter volume in anterior cingulate cortex, insula, and right temporo-parietal cortex. Patients with greater than median grey matter volume in this system had faster rates of improvement and significantly lower residual symptom scores after 8 weeks' treatment. Faster improvement was also predicted by greater functional activation of anterior cingulate cortex. Baseline symptom severity was negatively correlated with greater grey matter volume in dorsal prefrontal and anterior midcingulate regions anatomically distinct from the pregenual and subgenual cingulate regions predicting treatment response.
Structural MRI measurements of anterior cingulate cortex could provide a useful predictor of antidepressant treatment response.

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Available from: John Suckling, Oct 04, 2015
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    • "This is also consistent with model proposed by Goldapple et al. (2004). Despite the increased interest sparked by neuroimaging studies that assessed brain modifications after psychotherapy (Fu et al. 2008; Schnell and Herpertz 2007; Schienle et al. 2009; Goldapple et al. 2004) and pharmacological treatment (Bremner et al. 2007; Brody et al. 1999; Chen et al. 2007; Davidson et al. 2003; Fu et al. 2004; Haldane et al. 2008; Jogia et al. 2008; Kalin et al. 1997; Kennedy et al. 2001; Mayberg et al. 2000; Pizzagalli et al. 2001; Saxena et al. 2003; Vlassenko et al. 2004; Goldapple et al. 2004), it is still unclear whether the same neural mechanisms underlie both PsyTh and DrugTh. Indeed, because of the great heterogeneity of these studies, especially regarding the type of psychiatric disorder and experimental paradigm, we are still far from reaching an unambiguous conclusion. "
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    ABSTRACT: The idea that modifications of affect, behavior and cognition produced by psychotherapy are mediated by biological underpinnings predates the advent of the modern neurosciences. Recently, several studies demonstrated that psychotherapy outcomes are linked to modifications in specific brain regions. This opened the debate over the similarities and dissimilarities between psychotherapy and pharmacotherapy. In this study, we used activation likelihood estimation meta-analysis to investigate the effects of psychotherapy (PsyTh) and pharmacotherapy (DrugTh) on brain functioning in Major Depression (MD). Our results demonstrate that the two therapies modify different neural circuits. Specifically, PsyTh induces selective modifications in the left inferior and superior frontal gyri, middle temporal gyrus, lingual gyrus and middle cingulate cortex, as well as in the right middle frontal gyrus and precentral gyrus. Otherwise, DrugTh selectively affected brain activation in the right insula in MD patients. These results are in line with previous evidence of the synergy between psychotherapy and pharmacotherapy but they also demonstrate that the two therapies have different neural underpinnings.
    Brain Imaging and Behavior 07/2015; DOI:10.1007/s11682-015-9429-x · 4.60 Impact Factor
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    • "The disorder specific trajectory will help to consolidate and clarify the existing diagnosis derived from symptoms alone, especially when the symptoms are similar between several morbidities. The trajectory could possibly help to verify treatment effect, as an individual positive responder to a treatment may show a trajectory different to an individual who does not respond to a treatment (Chen et al., 2007). "
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    ABSTRACT: Background: Major psychiatric disorders are increasingly being conceptualized as 'neurodevelopmental', because they are associated with aberrant brain maturation. Several studies have hypothesized that a brain maturation index integrating patterns of neuroanatomical measurements may reliably identify individual subjects deviating from a normative neurodevelopmental trajectory. However, while recent studies have shown great promise in developing accurate brain maturation indices using neuroimaging data and multivariate machine learning techniques, this approach has not been validated using a large sample of longitudinal data from children and adolescents. Methods: T1-weighted scans from 303 healthy subjects aged 4.88 to 18.35years were acquired from the National Institute of Health (NIH) pediatric repository ( Out of the 303 subjects, 115 subjects were re-scanned after 2years. The least absolute shrinkage and selection operator algorithm (LASSO) was 'trained' to integrate neuroanatomical changes across chronological age and predict each individual's brain maturity. The resulting brain maturation index was developed using first-visit scans only, and was validated using second-visit scans. Results: We report a high correlation between the first-visit chronological age and brain maturation index (r=0.82, mean absolute error or MAE=1.69years), and a high correlation between the second-visit chronological age and brain maturation index (r=0.83, MAE=1.71years). The brain maturation index captured neuroanatomical volume changes between the first and second visits with an MAE of 0.27years. Conclusions: The brain maturation index developed in this study accurately predicted individual subjects' brain maturation longitudinally. Due to its strong clinical potentials in identifying individuals with an abnormal brain maturation trajectory, the brain maturation index may allow timely clinical interventions for individuals at risk for psychiatric disorders.
    NeuroImage 05/2015; 117. DOI:10.1016/j.neuroimage.2015.05.071 · 6.36 Impact Factor
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    • "A World Mental Health Survey conducted in 17 countries found that on average about 1 in 20 people reported having an episode of depression sometime in their life [1], and it is estimated that depression will constitute the second largest burden of disease by the year 2020 [2]. A large amount of brain imaging research has been focused on the neural correlates of depression using experiments that monitor emotions [3] [4] [5]. * Corresponding author. "
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    ABSTRACT: Several abnormal brain regions are known to be linked to depression, including amygdala, orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC) etc. The aim of this study is to apply EEG (electroencephalogram) data analysis to investigate, with respect to mild depression, whether there exists dysregulation in these brain regions. EEG sources were assessed from 9 healthy and 9 mildly depressed subjects who were classified according to the Beck Depression Inventory (BDI) criteria. t-Test was used to calculate the eye movement data and standardized low resolution tomography (sLORETA) was used to correlate EEG activity. A comparison of eye movement data between the healthy and mild depressed subjects exhibited that mildly depressed subjects spent more time viewing negative emotional faces. Comparison of the EEG from the two groups indicated higher theta activity in BA6 (Brodmann area) and higher alpha activity in BA38. EEG source location results suggested that temporal pole activity to be dysregulated, and eye-movement data analysis exhibited mild depressed subjects paid much more attention to negative face expressions, which is also in accordance with the results of EEG source location. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
    Computer methods and programs in biomedicine 04/2015; 120(3). DOI:10.1016/j.cmpb.2015.04.009 · 1.90 Impact Factor
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