{"title":"A unified pathogenic hypothesis for mental disorders based on schismogenesis","authors":"Mauro García-Toro , Rocío Gómez-Juanes","doi":"10.1016/j.biosystems.2025.105431","DOIUrl":null,"url":null,"abstract":"<div><div>Major Depressive Disorder, Bipolar Disorder, and Schizophrenia, share significant genetic, epigenetic, and phenotypic overlap, manifesting as dimensional psychopathology and convergent neuroimaging findings. These shared features have led to various models exploring common underlying pathophysiological mechanisms, including excitatory-inhibitory imbalance, the triple network model, network analysis, and social disconnection. While these models offer valuable insights, a unifying framework remains elusive.</div><div>Schismogenesis, a transdisciplinary construct, is proposed to reconcile divergent perspectives on mental health conditions. Characterized by positive feedback loops leading to functional dissociation due to insufficient inhibitory control, complementary schismogenesis results in rigid hyperactivation and hypoactivation within neural, cognitive, and social networks, compromising system flexibility. This pathological process underlies the core features of Major Depressive Disorder, Bipolar Disorder, and Schizophrenia, depending on its location within networks. The schismogenesis hypothesis suggests that when individuals are overwhelmed by excessive stress or tension, they may experience a breakdown or disconnection to prevent irreversible damage, reflecting evolutionary adaptations. Importantly, the potential reversibility of schismogenesis, particularly through interventions that facilitate system reintegration, suggests promising therapeutic avenues for further exploration.</div></div>","PeriodicalId":50730,"journal":{"name":"Biosystems","volume":"250 ","pages":"Article 105431"},"PeriodicalIF":2.0000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biosystems","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0303264725000413","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Major Depressive Disorder, Bipolar Disorder, and Schizophrenia, share significant genetic, epigenetic, and phenotypic overlap, manifesting as dimensional psychopathology and convergent neuroimaging findings. These shared features have led to various models exploring common underlying pathophysiological mechanisms, including excitatory-inhibitory imbalance, the triple network model, network analysis, and social disconnection. While these models offer valuable insights, a unifying framework remains elusive.
Schismogenesis, a transdisciplinary construct, is proposed to reconcile divergent perspectives on mental health conditions. Characterized by positive feedback loops leading to functional dissociation due to insufficient inhibitory control, complementary schismogenesis results in rigid hyperactivation and hypoactivation within neural, cognitive, and social networks, compromising system flexibility. This pathological process underlies the core features of Major Depressive Disorder, Bipolar Disorder, and Schizophrenia, depending on its location within networks. The schismogenesis hypothesis suggests that when individuals are overwhelmed by excessive stress or tension, they may experience a breakdown or disconnection to prevent irreversible damage, reflecting evolutionary adaptations. Importantly, the potential reversibility of schismogenesis, particularly through interventions that facilitate system reintegration, suggests promising therapeutic avenues for further exploration.
期刊介绍:
BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.