Emotion-cognition dysregulation in major depression: Multidimensional biases, neural circuit imbalance, and translational opportunities

Major depressive disorder is increasingly conceptualized as a disorder of emotion-cognition dysregulation. Convergent evidence shows reliable negative biases in recognition and attention (facilitated capture by threat, impaired disengagement), overgeneral and negatively weighted autobiographical memory, blunted processing of positive/rewarding stimuli, and preferential reliance on maladaptive regulation strategies (rumination, suppression). At the systems level, task-based and resting-state functional magnetic resonance imaging support the presence of a limbic-prefrontal imbalance - amygdala/insula hyperreactivity with reduced top-down control from dorsolateral/ventromedial prefrontal cortex and anterior cingulate - accompanied by large-scale network disruption (default-mode hyperconnectivity and weakened coupling to salience and frontoparietal control networks). Electrophysiology adds temporal specificity: Enhanced early components to negative faces (e.g. , N170), reduced late positive potential to appetitive cues, diminished prefrontal theta power, altered gamma activity, and perturbed theta-gamma coupling. Mechanistic contributors include monoaminergic imbalance, hypothalamic-pituitary-adrenal-axis activation, inflammatory signaling, and excitatory-inhibitory disequilibrium, moderated by cognitive style, early adversity, sex, and age. Translational opportunities span composite behavioral-neural signatures for diagnosis and stratification, risk forecasting, and treatment selection/monitoring; partial normalization of biases and circuits has been observed with cognitive behavioral therapy, selective serotonin reuptake inhibitor/serotonin-norepinephrine reuptake inhibitor, and noninvasive neuromodulation (repetitive transcranial magnetic stimulation/transcranial direct current stimulation), especially with imaging-guided targeting. Priorities include standardized paradigms, longitudinal multimodal designs, and mechanistic modeling to qualify biomarkers and enable mechanism-guided, precision interventions.