Background The mechanisms that contribute to emotion dysregulation in anxiety disorders are not well understood. Two common disorders, Generalized Anxiety Disorder (GAD) and Panic Disorder (PD), were examined to test the hypothesis that both disorders are characterized by hypo-activation in prefrontal cortex (PFC) during emotion regulation. A competing hypothesis that GAD in particular is characterized by PFC hyper-activation during emotion regulation (reflecting overactive top-down control) also was evaluated. Methods Twenty-two medication-free Healthy Control (HC), 23 GAD, and 18 PD participants underwent functional magnetic resonance imaging (fMRI) during a task that required them to reappraise (i.e., reduce) or maintain emotional responses to negative images. Results GAD participants reported the least reappraisal use in daily life, and reappraisal use was inversely associated with anxiety severity and functional impairment in these participants. During fMRI, HC demonstrated greater activation during both reappraisal and maintenance than either GAD or PD (who did not differ) in brain areas important for emotion regulation (e.g., dorsolateral and dorsomedial PFC). Furthermore, across all anxious participants, activation during reappraisal in dorsolateral and dorsomedial PFC was inversely associated with anxiety severity and functional impairment. Conclusions Emotion dysregulation in GAD and PD may be the consequence of PFC hypo-activation during emotion regulation, consistent with insufficient top-down control. The relationship between PFC hypo-activation and functional impairment suggests that the failure to engage PFC during emotion regulation may be part of the critical transition from dispositionally high anxiety to an anxiety disorder.

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The possibility of individualized treatment prediction has profound implications for the development of personalized interventions for patients with anxiety disorders. Here we utilize random forest classification and pre-treatment functional magnetic resonance imaging (fMRI) data from individuals with generalized anxiety disorder (GAD) and panic disorder (PD) to generate individual subject treatment outcome predictions. Before cognitive behavioral therapy (CBT), 48 adults (25 GAD and 23 PD) reduced (via cognitive reappraisal) or maintained their emotional responses to negative images during fMRI scanning. CBT responder status was predicted using activations from 70 anatomically defined regions. The final random forest model included 10 predictors contributing most to classification accuracy. A similar analysis was conducted using the clinical and demographic variables. Activations in the hippocampus during maintenance and anterior insula, superior temporal, supramarginal, and superior frontal gyri during reappraisal were among the best predictors, with greater activation in responders than non-responders. The final fMRI-based model yielded 79% accuracy, with good sensitivity (0.86), specificity (0.68), and positive and negative likelihood ratios (2.73, 0.20). Clinical and demographic variables yielded poorer accuracy (69%), sensitivity (0.79), specificity (0.53), and likelihood ratios (1.67, 0.39). This is the first use of random forest models to predict treatment outcome from pre-treatment neuroimaging data in psychiatry. Together, random forest models and fMRI can provide single-subject predictions with good test characteristics. Moreover, activation patterns are consistent with the notion that greater activation in cortico-limbic circuitry predicts better CBT response in GAD and PD.

These preliminary results highlight a common neural basis for clinical anxiety in these diagnoses and also suggest the presence of disorder-specific dysfunction.

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