Scary symptoms? Functional magnetic resonance imaging evidence for symptom interpretation bias in pathological health anxiety

Zhang, Yan; Witthöft, Michael; Bailer, Josef; Diener, Carsten; Mier, Daniela

doi:10.1007/s00406-017-0832-8

Cited by 10 publications

(8 citation statements)

References 65 publications

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“…These blocks were associated with greater recruitment of frontoparietal regions implicated in the task-based network and in executive control, left-lateralized semantic/linguistic processing (e.g., Broca’s area), and visual processing (Figure 2; Table 4). Consistent with the theoretical foundation for the IAT, and convergent with a few smaller neuroimaging IAT studies in nondepressed samples (Ballard et al, 2019; Egenolf et al, 2013; Mier et al, 2016; Yan et al, 2019), this neural pattern suggests behavioral responses during negative = me/positive = not me blocks produced an increased neural demand for response conflict resolution and/or elaborative semantic processing. Such neural patterns would be predicted when mental associations between two constructs (“me” and negative items) are relatively loose, less automated, or less prepotent.…”

Section: Discussionsupporting

confidence: 80%

“…Both neuroimaging and computational modeling techniques have the potential to reveal unique insights regarding the component neurocognitive processes that contribute to behavioral performance patterns on the task, providing insights into the nature of the task as well as potential brain-based, neurocomputational treatment targets. A few small neuroimaging IAT studies have been conducted to date, including studies of implicit self-associations conducted in healthy samples (Ballard et al, 2019; Egenolf et al, 2013) and studies of associations between harm and bodily symptoms in patients with and without health anxiety (Mier et al, 2016; Yan et al, 2019). Findings collectively suggest that during “incongruent” IAT blocks (i.e., when behavioral responses are routinely slowed due to “incongruent” key-mapping pairings), this is associated with an increased neural demand for cognitive control and executive or “task”-relevant networks.…”

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confidence: 99%

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Repeated measurement of implicit self-associations in clinical depression: Psychometric, neural, and computational properties.

Price¹,

Panny²,

Degutis³

et al. 2021

Journal of Abnormal Psychology

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Implicit self-associations are theorized to be rigidly and excessively negative in affective disorders like depression. Such information processing patterns may be useful as an approach to parsing heterogeneous etiologies, substrates, and treatment outcomes within the broad syndrome of depression. However, there is a lack of sufficient data on the psychometric, neural, and computational substrates of Implicit Association Test (IAT) performance in patient populations. In a treatment-seeking, clinically depressed sample (n ϭ 122), we administered five variants of the IAT-a dominant paradigm used in hundreds of studies of implicit cognition to date-at two repeated sessions (outside and inside a functional MRI scanner). We examined reliability, clinical correlates, and neural and computational substrates of IAT performance. IAT scores showed adequate (.67-.81) split-half reliability and convergent validity with one another and with relevant explicit symptom measures. Test-retest correlations (in vs. outside the functional MRI scanner) were present but modest (.15-.55). In depressed patients, on average, negative implicit self-representations appeared to be weaker or less efficiently processed relative to positive self-representations; elicited greater recruitment of frontoparietal task network regions; and, according to computational modeling of trial-by-trial data, were driven primarily by differential efficiency of information accumulation for negative and positive attributes. Greater degree of discrepancy between implicit and explicit self-worth predicted depression severity. Overall, these IATs show potential utility in understanding heterogeneous substrates of depression but leave substantial room for improvement. The observed clinical, neural, and computational correlates of implicit self-associations offer novel insights into a simple computer-administered task in a clinical population and point toward heterogeneous depression mechanisms and treatment targets.

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Section: Discussionsupporting

confidence: 80%

mentioning

confidence: 99%

Repeated measurement of implicit self-associations in clinical depression: Psychometric, neural, and computational properties.

Price¹,

Panny²,

Degutis³

et al. 2021

Journal of Abnormal Psychology

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“…This cerebral region is part of the prefrontal-parietal network [ 7 ] associated with sensory information, in which response-relevant information from the top-down promotes flexible, goal-directed behavior [ 59 ]. Studies in healthy controls and individuals with pathological health anxiety have revealed that a hyper-activated parietal cortex is implicated in implicit emotional processing [ 60 , 61 ]. As the prefrontal cortex and parietal cortex are the two important parts of frontoparietal network involving in implicit cognitive reappraisal [ 23 ], the increased activity of parietal cortex may be a compensatory mechanism for reduced recruitment of dlPFC and dmPFC during implicit reappraisal.…”

Section: Discussionmentioning

confidence: 99%

Neural basis of implicit cognitive reappraisal in panic disorder: an event-related fMRI study

Wang

et al. 2021

J Transl Med

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Background Panic disorder (PD) is thought to be related with deficits in emotion regulation, especially in cognitive reappraisal. According to the cognitive model, PD patients’ intrinsic and unconscious misappraisal strategies are the cause of panic attacks. However, no studies have yet been performed to explore the underlying neuromechanism of cognitive reappraisal that occur on an unconscious level in PD patients. Methods Twenty-six patients with PD and 25 healthy controls (HC) performed a fully-verified event-block design emotional regulation task aimed at investigating responses of implicit cognitive reappraisal during an fMRI scan. Participants passively viewed negatively valanced pictures that were beforehand neutrally, positively, or adversely portrayed in the task. Results Whole-brain analysis of fMRI data showed that PD patients exhibited less activation in the right dorsolateral prefrontal cortex (dlPFC) and right dorsomedial prefrontal cortex (dmPFC) compared to HC, but presented greater activation in parietal cortex when negative pictures were preceded by positive/neutral vs negative descriptions. Simultaneously, interactive effects of Group × Condition were observed in the right amygdala across both groups. Furthermore, activation in dlPFC and dmPFC was is negatively correlated to severity of anxiety and panic in PD when negative images were preceded by non-negative vs negative descriptions. Conclusions Emotional dysregulation in PD is likely the result of deficient activation in dlPFC and dmPFC during implicit cognitive reappraisal, in line with impaired automatic top-down regulation. Correlations between severity of anxiety and panic attack and activation of right dlPFC and dmPFC suggest that the failure to engage prefrontal region during implicit cognitive reappraisal might be associated wtih the severity of anxiety and panic; such functional patterns might be the target of possible treatments.

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“…Based on the notion that stronger associations cause longer reaction times (RTs) and require more cognitive control during the incongruent than congruent pairings (Greenwald et al ., 1998), the extent of automatic associations of in-ethnicity and in-team members can be easily investigated. Previous studies revealed that, by comparing the incongruent and congruent pairings, higher activation in the dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC) are apparent indicators of stronger implicit associations (Fedorenko et al ., 2013; Yan et al ., 2019). However, to our knowledge, this approach has not been used to investigate differences in strength of associations in the in-ethnicity vs in-team bias.…”

Section: Introductionmentioning

confidence: 99%

The effect of ethnicity and team membership on face processing: a cultural neuroscience perspective

Zhang

Schmidt

Saur

et al. 2019

Social Cognitive and Affective Neuroscience

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In-ethnicity bias, as one of the in-group biases, is widespread in different cultures, interfering with cross-ethnicity communication. Recent studies have revealed that an in-ethnicity bias can be reduced by an in-team bias caused by the membership in a mixed-ethnicity team. However, the neural correlates of different in-group biases are still not clear, especially regarding possible cultural differences. A total of 44 participants (20 Chinese and 24 Germans) were recruited and completed a social categorization fMRI-task, categorizing faces according to their ethnicity and a learned team membership. Our behavioral results revealed both in-ethnicity and in-team bias in German participants, but not in Chinese participants. Our imaging results, however, showed both biases across all participants, as reflected in increased dorsal medial frontal cortex (MFC) activation for in-ethnicity, as well as in-team categorizations, while activation in ventral MFC was higher for in-ethnicity faces in Chinese participants than in the German participants. Our results highlight the importance of the dorsal MFC for in-group categorization across cultures and suggest that cultures might modulate in-group biases.

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Scary symptoms? Functional magnetic resonance imaging evidence for symptom interpretation bias in pathological health anxiety

Cited by 10 publications

References 65 publications

Repeated measurement of implicit self-associations in clinical depression: Psychometric, neural, and computational properties.

Repeated measurement of implicit self-associations in clinical depression: Psychometric, neural, and computational properties.

Neural basis of implicit cognitive reappraisal in panic disorder: an event-related fMRI study

The effect of ethnicity and team membership on face processing: a cultural neuroscience perspective

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