Neural connectivity during affect labeling predicts treatment response to psychological therapies for social anxiety disorder

Young, Katherine S.; LeBeau, Richard T.; Niles, Andrea N.; Hsu, Kean J.; Burklund, Lisa J.; Mesri, Bita; Saxbe, Darby; Lieberman, Matthew D.; Craske, Michelle G.

doi:10.1016/j.jad.2018.08.016

Cited by 21 publications

(10 citation statements)

References 46 publications

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“…Several reports have also highlighted functional or structural properties of the amygdala that are impacted by CBT, often correlating with improvements in clinical outcomes 22 , 26 – 28 . And, paralleling the Whitfield-Gabrielli et al findings studied here, two other studies have reported that different features of amygdala function predict SAD treatment response to CBT 29 , 30 . Yet, to our knowledge, none of these studies have been directly subjected to independent replication attempts.…”

supporting

confidence: 85%

“…We believe it is important to replicate precisely defined models 70 . For example, the amygdala is a sensible focus point for predictive models relating to SAD, given the large body of research indicating amygdala alterations in SAD and other anxiety disorders 24 , 25 , and with several studies reporting that features of amygdala function predict CBT response in SAD patients 1 , 29 , 30 . However, the particular predictive amygdala features have varied widely from study to study, often with little overlap.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Brain markers predicting response to cognitive‐behavioral therapy for social anxiety disorder: an independent replication of Whitfield-Gabrieli et al. 2015

Ashar¹,

Clark²,

Gunning³

et al. 2021

Transl Psychiatry

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Predictive brain markers promise a number of important scientific, clinical, and societal applications. Over 600 predictive brain markers have been described in published reports, but very few have been tested in independent replication attempts. Here, we conducted an independent replication of a previously published marker predicting treatment response to cognitive-behavioral therapy for social anxiety disorder from patterns of resting-state fMRI amygdala connectivity1. The replication attempt was conducted in an existing dataset similar to the dataset used in the original report, by a team of independent investigators in consultation with the original authors. The precise model described in the original report positively predicted treatment outcomes in the replication dataset, but with marginal statistical significance, permutation test p = 0.1. The effect size was substantially smaller in the replication dataset, with the model explaining 2% of the variance in treatment outcomes, as compared to 21% in the original report. Several lines of evidence, including the current replication attempt, suggest that features of amygdala function or structure may be able to predict treatment response in anxiety disorders. However, predictive models that explain a substantial amount of variance in independent datasets will be needed for scientific and clinical applications.

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supporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Brain markers predicting response to cognitive‐behavioral therapy for social anxiety disorder: an independent replication of Whitfield-Gabrieli et al. 2015

Ashar¹,

Clark²,

Gunning³

et al. 2021

Transl Psychiatry

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“…19 (Fitzgerald et al, 2017b) Non-significant results 20 (Schmitt et al, 2016) Non-significant results 21 (Light et al, 2011) Non-significant results 22 (Yip et al, 2018) Non-significant results 23 (Hilland et al, 2018) Lacking healthy controls 24 Lacking healthy controls Table S1. List of excluded studies with reasons 25 (Contreras-Rodríguez et al, 2020) Lacking healthy controls 26 (Fitzgerald et al, 2019) Lacking healthy controls 27 (Schmitgen et al, 2019) Lacking healthy controls 28 (Gorka et al, 2019) Lacking healthy controls 29 (Klumpp et al, 2017b) Lacking healthy controls 30 (Fonzo et al, 2017b) Lacking healthy controls 31 (Fonzo et al, 2017a) Lacking healthy controls 32 (Klumpp et al, 2017a) Lacking healthy controls 33 (Reinecke et al, 2018) Lacking healthy controls 34 (Klumpp et al, 2017c) Lacking healthy controls 35 (Goldin et al, 2014) Lacking healthy controls 36 (Reinecke et al, 2014) Lacking healthy controls 37 (Brühl et al, 2013) Lacking healthy controls 38 (Goldin et al, 2013a) Lacking healthy controls 39 (Heller et al, 2013) Lacking healthy controls 40 (Goldin et al, 2013b) Lacking healthy controls 41 (Hermann et al, 2009) Lacking healthy controls 42 (Kanske et al, 2015) Non-whole-brain analysis 43 (Rabinak et al, 2014) Non-whole-brain analysis 44 (Kanske et al, 2012) Non-whole-brain analysis 45 (Lang et al, 2012) Non-whole-brain analysis 46 (Erk et al, 2010) Non-whole-brain analysis 47 (Douw et al, 2020) Non-whole-brain analysis 48 (Klumpp et al, 2019) Non-whole-brain analysis 49 (Jacob et al, 2019) Non-whole-brain analysis 50 (Young et al, 2019) Non-whole-brain analysis 51 (Zhang et al, 2018) Non-whole-brain analysis 52 …”

Section: Resultsmentioning

confidence: 99%

In search of convergent regional brain abnormality in cognitive emotion regulation: a transdiagnostic neuroimaging meta-analysis

khodadadifar¹,

Soltaninejad²,

Ebneabbasi³

et al. 2020

Preprint

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Cognitive emotion regulation (i.e., reappraisal) impairment is a key feature in a wide variety of mental disorders, suggesting common nature of disruption across psychiatric diagnoses. However, the extent of potential shared neurobiological disturbances related to reappraisalimpairment is incompletely understood. This study, therefore, aimed to identify neurobiological substrates of disturbed reappraisal using a transdiagnostic approach by performing a quantitative coordinate-based meta-analysis (CBMA) on reappraisal tasks across various mental disorders. Following the best-practice guidelines for neuroimaging meta-analysis, we systematicallysearched PubMed, ScienceDirect and Web of Science databases for whole-brain neuroimaging studies published through February 2020 that compared brain activation in patients with mental disorders and matched healthy controls during a reappraisal task. Out of 1608 publications, we retrieved 32 publications with 1240 unique individuals, providing sufficient power for conducting CBMA using activation likelihood estimation (ALE) method. The reported peak coordinates for the patient/control difference in selected articles were extracted and several ALE analyses were performed to identify spatial convergence. Surprisingly, neither the pooled ALE analysis noradditional analyses restricting to in-/decreased contrasts and more homogeneous grouping of coordinates (i.e., regulation direction, stimulus valence and disorder category) provided significant convergent findings. This CBMA indicates a lack of convergent regional abnormality related to reappraisal across various mental disorders. This might be due to the complex nature of reappraisal, heterogeneous clinical populations or methodological flexibility including preprocessing and analytical methods.

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“…Depressed participants are able to upregulate or dampen the activity and connectivity of regions involved in emotional processing (e.g., amygdala) by focusing on memories or imagery while viewing their fMRI signals. Following this technique, patients show reduced depression symptoms and long‐term changes in the brain (Young et al, 2018). Another study found that depressed men exhibit greater functional connectivity between the amygdala and prefrontal areas following neurofeedback training; further, this connectivity change was positively associated with symptom improvement (Zotev, 2011).…”

Section: Emerging Work and Future Directions: Toward A Precision Mentmentioning

confidence: 99%

Research Review: Brain network connectivity and the heterogeneity of depression in adolescence – a precision mental health perspective

Chahal

Gotlib

Guyer

2020

Child Psychology Psychiatry

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Background Adolescence is a period of high risk for the onset of depression, characterized by variability in symptoms, severity, and course. During adolescence, the neurocircuitry implicated in depression continues to mature, suggesting that it is an important period for intervention. Reflecting the recent emergence of ‘precision mental health’ – a person‐centered approach to identifying, preventing, and treating psychopathology – researchers have begun to document associations between heterogeneity in features of depression and individual differences in brain circuitry, most frequently in resting‐state functional connectivity (RSFC). Methods In this review, we present emerging work examining pre‐ and post‐treatment measures of network connectivity in depressed adolescents; these studies reveal potential intervention‐specific neural markers of treatment efficacy. We also review findings from studies examining associations between network connectivity and both types of depressive symptoms and response to treatment in adults, and indicate how this work can be extended to depressed adolescents. Finally, we offer recommendations for research that we believe will advance the science of precision mental health of adolescence. Results Nascent studies suggest that linking RSFC‐based pathophysiological variation with effects of different types of treatment and changes in mood following specific interventions will strengthen predictions of prognosis and treatment response. Studies with larger sample sizes and direct comparisons of treatments are required to determine whether RSFC patterns are reliable neuromarkers of treatment response for depressed adolescents. Although we are not yet at the point of using RSFC to guide clinical decision‐making, findings from research examining the stability and reliability of RSFC point to a favorable future for network‐based clinical phenotyping. Conclusions Delineating the correspondence between specific clinical characteristics of depression (e.g., symptoms, severity, and treatment response) and patterns of network‐based connectivity will facilitate the development of more tailored and effective approaches to the assessment, prevention, and treatment of depression in adolescents.

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Neural connectivity during affect labeling predicts treatment response to psychological therapies for social anxiety disorder

Cited by 21 publications

References 46 publications

Brain markers predicting response to cognitive‐behavioral therapy for social anxiety disorder: an independent replication of Whitfield-Gabrieli et al. 2015

Brain markers predicting response to cognitive‐behavioral therapy for social anxiety disorder: an independent replication of Whitfield-Gabrieli et al. 2015

In search of convergent regional brain abnormality in cognitive emotion regulation: a transdiagnostic neuroimaging meta-analysis

Research Review: Brain network connectivity and the heterogeneity of depression in adolescence – a precision mental health perspective

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