Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, USA; Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile; Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina; Trinity College Dublin, Dublin, Ireland.
Mental Health Center, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China; Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, People's Republic of China; Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada.
Neurosci Biobehav Rev. 2024 Feb;157:105510. doi: 10.1016/j.neubiorev.2023.105510. Epub 2023 Dec 15.
The cognitive neuroscience of brain diseases faces challenges in understanding the complex relationship between brain structure and function, the heterogeneity of brain phenotypes, and the lack of dimensional and transnosological explanations. This perspective offers a framework combining the predictive coding theory of allostatic interoceptive overload (PAIO) and the intrinsic neural timescales (INT) theory to provide a more dynamic understanding of brain health in psychiatry and neurology. PAIO integrates allostasis and interoception to assess the interaction between internal patterns and environmental stressors, while INT shows that different brain regions operate on different intrinsic timescales. The allostatic overload can be understood as a failure of INT, which involves a breakdown of proper temporal integration and segregation. This can lead to dimensional disbalances between exteroceptive/interoceptive inputs across brain and whole-body levels (cardiometabolic, cardiovascular, inflammatory, immune). This approach offers new insights, presenting novel perspectives on brain spatiotemporal hierarchies and interactions. By integrating these theories, the paper opens innovative paths for studying brain health dynamics, which can inform future research in brain health and disease.
脑疾病的认知神经科学在理解脑结构和功能之间的复杂关系、脑表型的异质性以及缺乏维度和跨疾病解释方面面临挑战。本观点提供了一个结合适应性内感受过载（PAIO）的预测编码理论和内在神经时间尺度（INT）理论的框架，为精神病学和神经病学中的脑健康提供了更具动态性的理解。PAIO 整合了适应性和内感受，以评估内部模式和环境应激源之间的相互作用，而 INT 则表明不同的脑区在不同的内在时间尺度上运作。适应性过载可以被理解为 INT 的失败，它涉及到适当的时间整合和分离的崩溃。这可能导致脑和全身水平（心脏代谢、心血管、炎症、免疫）的外感受/内感受输入之间的维度失衡。这种方法提供了新的见解，为脑时空层次结构和相互作用提供了新的视角。通过整合这些理论，本文为研究脑健康动力学开辟了创新途径，为脑健康和疾病的未来研究提供了信息。
