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大规模神经认知网络以及注意力、语言和记忆的分布式处理。

Large-scale neurocognitive networks and distributed processing for attention, language, and memory.

作者信息

Mesulam M M

机构信息

Department of Neurology, Beth Israel Hospital, Boston, MA 02215.

出版信息

Ann Neurol. 1990 Nov;28(5):597-613. doi: 10.1002/ana.410280502.

Abstract

Cognition and comportment are subserved by interconnected neural networks that allow high-level computational architectures including parallel distributed processing. Cognitive problems are not resolved by a sequential and hierarchical progression toward predetermined goals but instead by a simultaneous and interactive consideration of multiple possibilities and constraints until a satisfactory fit is achieved. The resultant texture of mental activity is characterized by almost infinite richness and flexibility. According to this model, complex behavior is mapped at the level of multifocal neural systems rather than specific anatomical sites, giving rise to brain-behavior relationships that are both localized and distributed. Each network contains anatomically addressed channels for transferring information content and chemically addressed pathways for modulating behavioral tone. This approach provides a blueprint for reexploring the neurological foundations of attention, language, memory, and frontal lobe function.

摘要

认知和行为由相互连接的神经网络支持,这些神经网络允许包括并行分布式处理在内的高级计算架构。认知问题不是通过朝着预定目标的顺序和分层进展来解决的,而是通过同时和交互式地考虑多种可能性和限制,直到达到令人满意的契合度。由此产生的心理活动结构具有几乎无限的丰富性和灵活性。根据这个模型,复杂行为映射在多焦点神经系统层面,而不是特定的解剖部位,从而产生既局部化又分布式的脑-行为关系。每个网络都包含用于传输信息内容的解剖学寻址通道和用于调节行为基调的化学寻址通路。这种方法为重新探索注意力、语言、记忆和额叶功能的神经学基础提供了一个蓝图。

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