Affective neural signatures do not distinguish women with emotion dysregulation from healthy controls: A mega-analysis across three task-based fMRI studies

Abstract

Pathophysiological models are urgently needed for personalized treatments of mental disorders. However, most potential neural markers for psychopathology are limited by low interpretability, prohibiting reverse inference from brain measures to clinical symptoms and traits. Neural signatures (i.e. multivariate brain-patterns trained to be both sensitive and specific to a construct of interest) might alleviate this problem, but are rarely applied to mental disorders. We tested whether previously developed neural signatures for negative affect and discrete emotions distinguish between healthy individuals and those with mental disorders characterized by emotion dysregulation, i.e. Borderline Personality Disorder (BPD) and complex Post-traumatic Stress Disorder (cPTSD). In three different fMRI studies, a total sample of 192 women (49 BPD, 62 cPTSD, 81 healthy controls) were shown pictures of scenes with negative or neutral content. Based on pathophysiological models, we hypothesized higher negative and lower positive reactivity of neural emotion signatures in participants with emotion dysregulation. The expression of neural signatures differed strongly between neutral and negative pictures (average Cohen's d = 1.17). Nevertheless, a mega-analysis on individual participant data showed no differences in the reactivity of neural signatures between participants with and without emotion dysregulation. Confidence intervals ruled out even small effect sizes in the hypothesized direction and were further supported by Bayes factors. Overall, these results support the validity of neural signatures for emotional states during fMRI tasks, but raise important questions concerning their link to individual differences in emotion dysregulation.

Anxiety-Related Frontocortical Activity Is Associated With Dampened Stressor Reactivity in the Real World

“…No, mechanistic work in humans, monkeys, and rodents makes it abundantly clear that they are Hur et al, 2019). Instead, this work raises the possibility that conventional fMRI measures of emotion perception (viewing photographs of fearful or angry faces) and generation (briefly waiting for aversive stimulation) are suboptimal probes of the aspects of subcortical function most relevant to everyday affect (i.e., "wrong" assay; Puccetti et al, 2021;Sicorello et al, 2021). Alternatively, it could be that isolated regional measures of subcortical function are only weakly predictive of conscious feelings of negative affect and, hence, to typical state, trait, and clinical assessments (Brown et al, 2019;Chang et al, 2015;.…”

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“…No, mechanistic work in humans, monkeys, and rodents makes it abundantly clear that they are (Fox & Shackman, 2019; Hur et al, 2019). Instead, this work raises the possibility that conventional fMRI measures of emotion perception ( viewing photographs of fearful or angry faces ) and generation ( briefly waiting for aversive stimulation ) are suboptimal probes of the aspects of subcortical function most relevant to everyday affect (i.e., ‘wrong’ assay) (Puccetti et al, 2021; Sicorello et al, 2021). Alternatively, it could be that isolated regional measures of subcortical function are only weakly predictive of conscious feelings of negative affect and, hence, to typical state, trait, and clinical assessments (Brown, Lau, & LeDoux, 2019; Chang et al, 2015; LeDoux & Pine, 2016; Shackman & Fox, 2018).…”

Improving treatment outcomes for borderline personality disorder: what can we learn from biomarker studies of psychotherapy?

“…With only one study of machine learning using neurobiological correlates in BPD treatment, this is also a promising area for future investigation [55]. More broadly in the field, data sharing and pooling of neuroimaging [56] and/ or genetic data in BPD, like other large-scale consortia have achieved via global working groups [57], will maximize resources and collaboration such as through mega-analytic studies [58], helping to overcome many methodological challenges to advance knowledge in the field.…”