Chronic pain is a global health challenge requiring a transition from "one-size-fits-all" protocols to personalized treatment approaches. Current neuroimaging evidence suggests that chronic pain pathophysiology is closely linked to the dysfunction of large-scale brain networks: the Default Mode Network (DMN), the Salience Network (SN), and the Central Executive Network (CEN). However, the integration of these findings into clinical psychotherapy remains limited.

The study aims to develop an operationalized neuropsychological model for personalized psychotherapy of chronic pain based on patient stratification into phenotypes of DMN/SN/CEN network dysfunction. A systematic review of scientific literature was conducted using PubMed, Scopus, and Web of Science databases for the period 2015—2025. The relationship between functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) markers and the efficacy of psychotherapeutic interventions (Cognitive Behavioral Therapy, Acceptance and Commitment Therapy, Mindfulness-Based Stress Reduction, neurofeedback) was analyzed.

It was established that chronic pain is characterized by DMN and SN hyperactivity coupled with CEN hypofunction. Based on neurophysiological markers, four stable neuropsychological phenotypes were identified: cognitive-dysregulatory, affective-hyperreactive, interoceptivedissociative, and limbic-depressive. It is argued that each phenotype requires specific interventions. Specifically, Cognitive Behavioral Therapy is most effective for restoring CEN control, while Mindfulness-Based Stress Reduction and Acceptance and Commitment Therapy target SN deactivation and DMN rumination correction.

The proposed model enables a shift from symptom-oriented to mechanism-oriented psychotherapy. Identifying an individual’s neuropsychological profile enhances the precision of psychotherapeutic selection, facilitating targeted neuroplasticity and improving the quality of life for patients with chronic pain.