内在时间尺度和预测性静态整体感应在大脑健康和疾病中
Agustin Ibanez1, Georg Northoff2
1Global 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.
Neuroscience and biobehavioral reviews
|December 17, 2023
概括
这项研究提出了一个新的框架来理解大脑健康,通过整合预测编码理论的全静态感官过载 (PAIO) 和内在神经时间尺度 (INT) 理论. 这种方法提供了对大脑疾病及其潜在机制的动态见解.
科学领域:
- 认知神经科学 认知神经科学
- 精神病学是一个精神病学.
- 神经学 神经学
背景情况:
- 认知神经科学面临的挑战包括理解大脑结构-功能关系,表型异质性以及对跨神经学解释的需求.
- 目前的模型很难捕捉到大脑健康和疾病的动态性质.
- 现有的理论缺乏统一的框架,以整合身体内部状态与外部环境因素.
研究的目的:
- 为理解大脑健康和疾病动态提供一种新的理论框架.
- 整合全静态感官过载 (PAIO) 的预测编码理论与内在神经时间尺度 (INT) 理论.
- 为精神病和神经系统疾病中大脑功能提供更具动态和维度的视角.
主要方法:
- 整合PAIO和INT理论的概念框架.
- PAIO评估身体内部状态 (内接收,静止) 和环境压力因素之间的相互作用.
- INT理论认为,不同的大脑区域在不同的内在时间尺度上运行.
主要成果:
- 全静态过载被概念化为INT的失败,导致时间整合和隔离受损.
- 这种失败会导致神经系统和身体系统传感输入的维度失衡.
- 综合框架为大脑的时空层次结构和相互作用提供了新的视角.
结论:
- 联合PAIO和INT框架提供了对大脑健康和疾病的动态理解.
- 这种方法为神经处理的时空动态提供了新的见解.
- 该框架为大脑健康和疾病的创新研究铺平了道路,有可能为诊断和治疗策略提供信息.
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