Disrupted self-referential processing and empathy-based interventions in mental disorders: neural mechanisms,...

Self-referential processing (SRP), the mental activity of linking experiences and stimuli to the self, is fundamental to shaping identity, regulating affect, and navigating complex social environments. Disruptions in SRP are increasingly recognized as a transdiagnostic hallmark across psychiatric disorders, including schizophrenia spectrum disorders, major depressive disorder, and anxiety disorders. Such disruptions often manifest as distorted self-perception, negative cognitive-affective biases, and dysfunctional connectivity within key neural networks, particularly the default mode network (DMN) and the medial prefrontal cortex (mPFC). Emerging evidence reveals a dynamic bidirectional relationship between SRP and empathy. Impairments in self-processing may hinder the capacity to accurately infer others' emotional and cognitive states, while deficits in empathic attunement may reinforce maladaptive self-focus. This interplay contributes to social withdrawal, interpersonal dysfunction, and emotional dysregulation across diagnostic boundaries. Recent therapeutic advances suggest that interventions targeting the interface between SRP and empathy may effectively modulate shared neurocognitive mechanisms. Such interventions include metacognitive therapy, mindfulness-based interventions, and psychedelic-assisted psychotherapy. These therapeutic approaches show preliminary but promising evidence for reducing maladaptive self-focused attention, enhancing emotion regulation, and improving social functioning. This review synthesizes empirical evidence regarding the neural underpinnings of SRP, delineates disorder-specific alterations in self-referential processing, and examines the bidirectional interplay between SRP and empathic functioning. We further outline a conceptual framework for empathy-based interventions targeting SRP dysfunction and propose future directions for precision psychiatry research. Emphasis is placed on developing personalized, mechanism-driven therapeutic strategies informed by computational modeling, transdiagnostic biomarker identification, and digital therapeutic platforms.