Lv Zhou, Zhengchang Jiang, Zhao Chang, Rong Wang, Ying Wu
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The resting-state brain showed a moderate degree of state transition at the whole-brain scale, but the regional heterogeneity of the transition was the highest, which functionally, was associated with the dynamic balance between segregation and integration, and structurally, was supported by hierarchical modules in brain structural connectivity. In addition, the high state transition among regions was supported by serotonin 1 A (5-HT<sub>1A</sub>) and dopamine (D<sub>2</sub>) receptors. Our findings highlight the critical role of brain state transition in cognitive abilities and reveal the underlying dynamic mechanisms, offering new insights into the functional principles of the resting brain.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11571-025-10347-6.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"163"},"PeriodicalIF":3.9000,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12496318/pdf/","citationCount":"0","resultStr":"{\"title\":\"Spatiotemporal transition of resting-state brain networks associates with human cognitive abilities.\",\"authors\":\"Lv Zhou, Zhengchang Jiang, Zhao Chang, Rong Wang, Ying Wu\",\"doi\":\"10.1007/s11571-025-10347-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The brain is a dynamic system that continuously switches between different states. This brain state transition has significant functional consequences on human cognition, but its dynamic mechanism is rarely understood. Here, we quantified the state transition by measuring the spatiotemporal reconfiguration of modular structure spanning time and space in the resting-brain functional networks. By integrating multimodal data, noise-driven large-scale dynamic model and meta-analysis, we found the significant relationship between state transition and brain evolution indicated by human accelerated regions (HARs) genes. This state transition was associated with diverse cognitive abilities, especially better executive control ability in the default mode network and control network. The resting-state brain showed a moderate degree of state transition at the whole-brain scale, but the regional heterogeneity of the transition was the highest, which functionally, was associated with the dynamic balance between segregation and integration, and structurally, was supported by hierarchical modules in brain structural connectivity. In addition, the high state transition among regions was supported by serotonin 1 A (5-HT<sub>1A</sub>) and dopamine (D<sub>2</sub>) receptors. 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Spatiotemporal transition of resting-state brain networks associates with human cognitive abilities.
The brain is a dynamic system that continuously switches between different states. This brain state transition has significant functional consequences on human cognition, but its dynamic mechanism is rarely understood. Here, we quantified the state transition by measuring the spatiotemporal reconfiguration of modular structure spanning time and space in the resting-brain functional networks. By integrating multimodal data, noise-driven large-scale dynamic model and meta-analysis, we found the significant relationship between state transition and brain evolution indicated by human accelerated regions (HARs) genes. This state transition was associated with diverse cognitive abilities, especially better executive control ability in the default mode network and control network. The resting-state brain showed a moderate degree of state transition at the whole-brain scale, but the regional heterogeneity of the transition was the highest, which functionally, was associated with the dynamic balance between segregation and integration, and structurally, was supported by hierarchical modules in brain structural connectivity. In addition, the high state transition among regions was supported by serotonin 1 A (5-HT1A) and dopamine (D2) receptors. Our findings highlight the critical role of brain state transition in cognitive abilities and reveal the underlying dynamic mechanisms, offering new insights into the functional principles of the resting brain.
Supplementary information: The online version contains supplementary material available at 10.1007/s11571-025-10347-6.
期刊介绍:
Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models.
The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome.
The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged.
1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics.
2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages.
3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.