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Multi-path neural mechanisms of self-other reward integration impairment in schizophrenia
ChaoZheng Huang1, HanBin Sang2, Xuan Zhao3
1School of Psychology, Northwest Normal University, Lanzhou 730070, China; School of Psychology, Sichuan Normal University, Chengdu 610068, China.
Abstract:
Schizophrenia is marked by social dysfunction and motivational deficits that are not fully explained by global reward impairment. Emerging evidence suggests that schizophrenia involves distributed abnormalities in reward processing and predictive updating, whose consequences may become especially pronounced when outcomes for self and others must be integrated within social decision-making. A concise, mechanistic framework linking these anomalies to neural and neuromodulatory systems is still lacking.This study integrated findings from experimental studies of social and nonsocial reinforcement learning, effort-based decision-making and self-other attribution in schizophrenia and related psychosis-spectrum conditions. These findings are combined with human neuroimaging and pharmacological evidence on reward and salience networks, and with work on social neuromodulators and predictive-processing models in social neuroscience. Four interacting mechanisms were identified: (1) imprecise predictive inferences about others' behaviour and joint outcomes; (2) aberrant salience and reward prediction-error signalling in midbrain-ventral striatal-ACC/insula circuits; (3) effort-cost computation that disfavors prosocial and long-term social actions; and (4)self-other boundaries disturbed, producing unreliable assignment of outcomes to self versus other. These pathways converge on dysfunction in mentalizing, salience/reward and control networks and appear shaped by dopaminergic, oxytocinergic and related neuromodulatory influences. Self-other reward integration impairment in schizophrenia reflects the joint impact of predictive, motivational and self-referential disturbances within specific neuromodulated circuits. Further empirical research will be needed in the future to test and expand the scope of this model.
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