Neural basis of the emotional Stroop interference effect in major depression

Neuroimaging Research Group, Clinical Neuroscience, Institute of Psychiatry, King's College London, UK.
Psychological Medicine (Impact Factor: 5.94). 03/2008; 38(2):247-56. DOI: 10.1017/S0033291707001523
Source: PubMed


A mood-congruent sensitivity towards negative stimuli has been associated with development and maintenance of major depressive disorder (MDD). The emotional Stroop task assesses interference effects arising from the conflict of emotional expressions consistent with disorder-specific self-schemata and cognitive colour-naming instructions. Functional neuroimaging studies of the emotional Stroop effect advocate a critical involvement of the anterior cingulate cortex (ACC) during these processes.
Subjects were 17 medication-free individuals with unipolar MDD in an acute depressive episode (mean age 39 years), and 17 age-, gender- and IQ-matched healthy volunteers. In an emotional Stroop task, sad and neutral words were presented in various colours, and subjects were required to name the colour of words whilst undergoing functional magnetic resonance imaging (fMRI). Overt verbal responses were acquired with a clustered fMRI acquisition sequence.
Individuals with depression showed greater increases in response time from neutral to sad words relative to controls. fMRI data showed a significant engagement of left rostral ACC (BA 32) and right precuneus during sad words in patients relative to controls. Additionally, rostral ACC activation was positively correlated with latencies of negative words in MDD patients. Healthy controls did not have any regions of increased activation compared to MDD patients.
These findings provide evidence for a behavioural and neural emotional Stroop effect in MDD and highlight the importance of the ACC during monitoring of conflicting cognitive processes and mood-congruent processing in depression.

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Available from: Nicholas David Walsh, Feb 25, 2014
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    • "The Emotional Stroop task continues to be widely used to study attentional biases for threat as a function of early childhood trauma (Wingenfeld et al., 2009), attachment (Atkinson et al., 2009), borderline personality disorder and posttraumatic stress disorder (Cisler et al., 2011), among others. It has also been used to identify the neural sources associated with emotion (Mitterschiffthaler et al., 2008). "
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    ABSTRACT: It is widely believed that threatening stimuli in our environment capture attention. Much of the core evidence for attentional capture by threatening stimuli comes from the Emotional Stroop task. Yet recent evidence suggests that the Emotional Stroop task does not measure attentional capture (e.g., Algom et al., 2004). The present paper assesses whether threat words can capture attention using a modified Stroop Dilution procedure (e.g., Kahneman & Chajczyk, 1983), where attentional capture by a threat word is inferred from a reduction in color-word interference for threat words compared to non-threat words (emotional Stroop Dilution). The outcome of the present experiments indicates that threat words can capture attention, but only when task demands do not require that a word be attended. It is suggested that threat words produce (1) cognitive slowing, and influence two processes of selective attention (2) attentional capture and (3) the ability to filter irrelevant dimensions of an attended stimulus. Copyright © 2015 Elsevier B.V. All rights reserved.
    Acta psychologica 07/2015; 159. DOI:10.1016/j.actpsy.2015.05.008 · 2.19 Impact Factor
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    • "As with structural findings, both medial and lateral prefrontal systems have been implicated. During negative affective processing tasks such as viewing sad or fearful faces, dorsolateral prefrontal areas reliably show reduced activation compared with controls,39–41 whereas the anterior cingulate cortex (ACC) shows increased activation.42–45 Functional alterations while processing negative stimuli have also been demonstrated in limbic regions, most notably in the amygdala, where exaggerated responses to negative stimuli are seen,40,43,46–49 whereas processing of positive stimuli such as monetary gains is associated with reduced activity in areas associated with reward processing such as the striatum.50–52 "
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    ABSTRACT: A growing number of studies have used neuroimaging to further our understanding of how brain structure and function are altered in major depression. More recently, these techniques have begun to show promise for the diagnosis and treatment of depression, both as aids to conventional methods and as methods in their own right. In this review, we describe recent neuroimaging findings in the field that might aid diagnosis and improve treatment accuracy. Overall, major depression is associated with numerous structural and functional differences in neural systems involved in emotion processing and mood regulation. Furthermore, several studies have shown that the structure and function of these systems is changed by pharmacological and psychological treatments of the condition and that these changes in candidate brain regions might predict clinical response. More recently, "machine learning" methods have used neuroimaging data to categorize individual patients according to their diagnostic status and predict treatment response. Despite being mostly limited to group-level comparisons at present, with the introduction of new methods and more naturalistic studies, neuroimaging has the potential to become part of the clinical armamentarium and may improve diagnostic accuracy and inform treatment choice at the patient level.
    Neuropsychiatric Disease and Treatment 08/2014; 10:1509-22. DOI:10.2147/NDT.S50156 · 1.74 Impact Factor
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    • "Higher severity of depression predicted increased activity to negative distractors in a region of dACC that was also active in the group response to incongruent distractors, and which has been shown to be involved in cognitive control in previous research (Dosenbach et al., 2006). This pattern of hyperactivity converges with other studies examining affective interference (Mitterschiffthaler et al., 2008; Wang et al., 2008) and is consistent with the idea that the task of ignoring negative task-irrelevant information is especially taxing at higher levels of depression. It may be that, because highly depressed individuals experience greater interference by negative material, they must recruit dACC to 'pick up the slack' in top-down control (e.g. "
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    ABSTRACT: Previous studies have shown that depressed individuals have difficulty directing attention away from negative distractors, a phenomenon known as affective interference. However, findings are mixed regarding the neural mechanisms and network dynamics of affective interference. The present study addressed these issues by comparing neural activation during emotion-word and color-word Stroop tasks in participants with varying levels of (primarily subclinical) depression. Depressive symptoms predicted increased activation to negative distractors in areas of dorsal anterior cingulate (dACC) and posterior cingulate (PCC) cortex, regions implicated in cognitive control and internally-directed attention, respectively. Increased dACC activity was also observed in the group-average response to incongruent distractors, suggesting that dACC activity during affective interference is related to overtaxed cognitive control. In contrast, regions of PCC were deactivated across the group in response to incongruent distractors, suggesting that PCC activity during affective interference represents task-independent processing. A psychophysiological interaction emerged in which higher depression predicted more positively correlated activity between dACC and PCC during affective interference, i.e., greater connectivity between cognitive control and internal-attention systems. These findings suggest that, when individuals high in depression are confronted by negative material, increased attention to internal thoughts and difficulty shifting resources to the external world interfere with goal-directed behavior.
    Social Cognitive and Affective Neuroscience 07/2014; 10(5). DOI:10.1093/scan/nsu100 · 7.37 Impact Factor
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