The neurobiology of human fear generalization: meta-analysis and working neural model

Webler, Ryan; Berg, Hannah; Fhong, Kimberly; Tuominen, Lauri; Holt, Daphne J.; Morey, Rajendra A.; Lange, Iris; Burton, Philip; Fullana, Miquel À.; Raduà, Joaquim; Lissek, Shmuel

doi:10.1016/j.neubiorev.2021.06.035

Cited by 103 publications

(40 citation statements)

References 165 publications

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“…The new approach is conceptually novel, but it involves only a minor modification of the “seed-based d mapping-permutation of subject images” (SDM-PSI) ( www.sdmproject.com ) ( 11 , 40 – 42 ), an already validated and widely used brain imaging meta-analytic method ( 43 – 51 ). The main advantage of this method is that it directly tests whether there are differences between patients and controls, rather than conducting indirect tests such as whether peaks tend to converge in some regions more than in others ( 52 ).…”

Section: Methods and Analysismentioning

confidence: 99%

Focusing on Comorbidity—A Novel Meta-Analytic Approach and Protocol to Disentangle the Specific Neuroanatomy of Co-occurring Mental Disorders

et al. 2022

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BackgroundIn mental health, comorbidities are the norm rather than the exception. However, current meta-analytic methods for summarizing the neural correlates of mental disorders do not consider comorbidities, reducing them to a source of noise and bias rather than benefitting from their valuable information.ObjectivesWe describe and validate a novel neuroimaging meta-analytic approach that focuses on comorbidities. In addition, we present the protocol for a meta-analysis of all major mental disorders and their comorbidities.MethodsThe novel approach consists of a modification of Seed-based d Mapping—with Permutation of Subject Images (SDM-PSI) in which the linear models have no intercept. As in previous SDM meta-analyses, the dependent variable is the brain anatomical difference between patients and controls in a voxel. However, there is no primary disorder, and the independent variables are the percentages of patients with each disorder and each pair of potentially comorbid disorders. We use simulations to validate and provide an example of this novel approach, which correctly disentangled the abnormalities associated with each disorder and comorbidity. We then describe a protocol for conducting the new meta-analysis of all major mental disorders and their comorbidities. Specifically, we will include all voxel-based morphometry (VBM) studies of mental disorders for which a meta-analysis has already been published, including at least 10 studies. We will use the novel approach to analyze all included studies in two separate single linear models, one for children/adolescents and one for adults.DiscussionThe novel approach is a valid method to focus on comorbidities. The meta-analysis will yield a comprehensive atlas of the neuroanatomy of all major mental disorders and their comorbidities, which we hope might help develop potential diagnostic and therapeutic tools.

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Section: Methods and Analysismentioning

confidence: 99%

Focusing on Comorbidity—A Novel Meta-Analytic Approach and Protocol to Disentangle the Specific Neuroanatomy of Co-occurring Mental Disorders

et al. 2022

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“…Notes: Regions of interest to be included here were selected based on a meta-analysis of seven fMRI fear generalization studies in psychiatrically healthy samples identified significant nodes within cingulo-opercular (salience) and frontoparietal (central executive, default mode) networks that compete to express or impede fearful behavior when confronted with a generalization stimulus (Webler et al, 2021). Primary regions of interest in these circuits include those related to the evaluation and awareness of threat (e.g., amygdala, insula, ACC dorsal medial prefrontal cortex [dmPFC]) and associated fear-related actions (e.g., caudate, supplementary motor area [SMA]).…”

Section: ↑ -↑mentioning

confidence: 99%

“…The reviewed fMRI data provide evidence for some, but not all, of the cingulo-opercular and frontoparietal regions implicated in studies of fear generalization in psychiatrically healthy people (Webler et al, 2021) as significantly related to an anxiety-related disorder during a fear generalization task (see Figure 4). The most consistent cross-study findings were hypoactive ventromedial prefrontal cortex (vmPFC), hyperactive striatal regions (e.g., caudate, putamen), and primarily hyperactivation in the insula to be related to anxiety-related disorders.…”

Section: ↑ -↑mentioning

confidence: 99%

“…This indicates a possible target for intervention: addressing hippocampal dysfunction to limit fear generalization. A recent comprehensive model, inspired in part by LeDoux's 'low road' hypothesis of threat processing (LeDoux, 1994), centers on the role of subcortical (e.g., thalamic, amygdala, locus coeruleus) responses to stimuli that resemble a learned threat triggering pattern completion processes in the hippocampus (Webler et al, 2021). When coupled with impaired prefrontal inhibitory regulation, rapid threat detection along with pattern completion are proposed to lead to heightened generalization in anxiety-related disorders.…”

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confidence: 99%

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A Meta-Analysis of Conditioned Fear Generalization in Anxiety-Related Disorders

Cooper¹,

Dis²,

Hagenaars³

et al. 2022

Preprint

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Objective: Generalization of conditioned fear is adaptive in some situations but maladaptive when fear excessively generalizes to innocuous stimuli with incidental resemblance to a genuine threat cue. Recently, empirical interest in fear generalization as a transdiagnostic explanatory mechanism underlying anxiety-related disorders has accelerated. As there are now several studies of fear generalization across multiple types of anxiety-related disorders, the authors conducted a meta-analysis of studies reporting behavioral measures (subjective ratings and psychophysiological indices) of fear generalization in anxiety-related disorder vs. comparison groups.Method: We conducted systematic searches of electronic databases (conducted from January-October 2020) for fear generalization studies involving anxiety-related disorder groups or subclinical analogue groups. A total of 300 records were full-text screened and two unpublished datasets were obtained, yielding 16 studies reporting behavioral fear generalization. Random-effects meta-analytic models and meta-regressions were applied to the behavioral data.Results: Fear generalization was significantly heightened in anxiety-related disorder participants (N=439) relative to comparison participants (N=428). We did not identify any significant clinical, sample, or methodological moderators. Conclusion: Heightened fear generalization is quantitatively supported as distinguishing anxiety-related disorder groups from comparison groups. Evidence suggests this effect is transdiagnostic, relatively robust to experimental or sample parameters, and that generalization paradigms are a well-supported framework for neurobehavioral investigations of learning and emotion in anxiety-related disorders. We discuss these findings in the context of prior meta-analyses and future directions and challenges for the field.

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“…Microstructural alterations of the caudate, which are associated with PTSD, are hypothesized to disrupt striatal-dependent learning of fear associations [ 17 ]. Reduced caudate volume is associated with early life stress, while increased caudate and thalamic activity are associated with overgeneralization of conditioned fear in PTSD [ 15 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume

et al. 2021

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The volume of subcortical structures represents a reliable, quantitative, and objective phenotype that captures genetic effects, environmental effects such as trauma, and disease effects such as posttraumatic stress disorder (PTSD). Trauma and PTSD represent potent exposures that may interact with genetic markers to influence brain structure and function. Genetic variants, associated with subcortical volumes in two large normative discovery samples, were used to compute polygenic scores (PGS) for the volume of seven subcortical structures. These were applied to a target sample enriched for childhood trauma and PTSD. Subcortical volume PGS from the discovery sample were strongly associated in our trauma/PTSD enriched sample (n = 7580) with respective subcortical volumes of the hippocampus (p = 1.10 × 10−20), thalamus (p = 7.46 × 10−10), caudate (p = 1.97 × 10−18), putamen (p = 1.7 × 10−12), and nucleus accumbens (p = 1.99 × 10−7). We found a significant association between the hippocampal volume PGS and hippocampal volume in control subjects from our sample, but was absent in individuals with PTSD (GxE; (beta = −0.10, p = 0.027)). This significant GxE (PGS × PTSD) relationship persisted (p < 1 × 10−19) in four out of five threshold peaks (0.024, 0.133, 0.487, 0.730, and 0.889) used to calculate hippocampal volume PGSs. We detected similar GxE (G × ChildTrauma) relationships in the amygdala for exposure to childhood trauma (rs4702973; p = 2.16 × 10−7) or PTSD (rs10861272; p = 1.78 × 10−6) in the CHST11 gene. The hippocampus and amygdala are pivotal brain structures in mediating PTSD symptomatology. Trauma exposure and PTSD modulate the effect of polygenic markers on hippocampal volume (GxE) and the amygdala volume PGS is associated with PTSD risk, which supports the role of amygdala volume as a risk factor for PTSD.

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The neurobiology of human fear generalization: meta-analysis and working neural model

Cited by 103 publications

References 165 publications

Focusing on Comorbidity—A Novel Meta-Analytic Approach and Protocol to Disentangle the Specific Neuroanatomy of Co-occurring Mental Disorders

Focusing on Comorbidity—A Novel Meta-Analytic Approach and Protocol to Disentangle the Specific Neuroanatomy of Co-occurring Mental Disorders

A Meta-Analysis of Conditioned Fear Generalization in Anxiety-Related Disorders

Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume

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