Suppr超能文献

从通过视觉构建进行空间导航到情景记忆和想象。

From spatial navigation via visual construction to episodic memory and imagination.

作者信息

Arbib Michael A

机构信息

University of California San Diego, San Diego, USA.

出版信息

Biol Cybern. 2020 Apr;114(2):139-167. doi: 10.1007/s00422-020-00829-7. Epub 2020 Apr 13.

Abstract

This hybrid of review and personal essay argues that models of visual construction are essential to extend spatial navigation models to models that link episodic memory and imagination. The starting point is the TAM-WG model, combining the Taxon Affordance Model and the World Graph model of spatial navigation. The key here is to reject approaches in which memory is restricted to unanalyzed views from familiar places, and their later recall. Instead, we will seek mechanisms for imagining truly novel scenes and episodes. We thus introduce a specific variant of schema theory and VISIONS, a cooperative computation model of visual scene understanding in which a scene is represented by an assemblage of schema instances with links to lower-level "patches" of relevant visual data. We sketch a new conceptual framework for future modeling, Visual Integration of Diverse Multi-Modal Aspects, by extending VISIONS from static scenes to episodes combining agents, actions and objects and assess its relevance to both navigation and episodic memory. We can then analyze imagination as a constructive process that combines aspects of memories of prior episodes along with other schemas and adjusts them into a coherent whole which, through expectations associated with diverse episodes and schemas, may yield the linkage of episodes that constitutes a dream or a narrative. The result is IBSEN, a conceptual model of Imagination in Brain Systems for Episodes and Navigation. The essay closes by analyzing other papers in this Special Issue to assess to what extent their results relate to the research proposed here.

摘要

这篇兼具综述与个人随笔性质的文章认为,视觉构建模型对于将空间导航模型扩展为连接情景记忆和想象的模型至关重要。文章开篇介绍了TAM-WG模型,它结合了分类群可供性模型和空间导航的世界图模型。关键在于摒弃那种将记忆局限于熟悉地点的未经分析的视图及其后续回忆的方法。相反,我们将探寻想象全新场景和情节的机制。因此,我们引入了图式理论的一个特定变体以及VISIONS,这是一种视觉场景理解的协作计算模型,其中一个场景由一组图式实例表示,并与相关视觉数据的低级“补丁”相链接。通过将VISIONS从静态场景扩展到包含主体、动作和物体的情节,我们勾勒出了一个用于未来建模的新的概念框架——多样多模态方面的视觉整合,并评估其与导航和情景记忆的相关性。然后,我们可以将想象分析为一个建设性过程,它将先前情节的记忆方面与其他图式相结合,并将它们调整为一个连贯的整体,这个整体通过与不同情节和图式相关的预期,可能产生构成梦境或叙事的情节联系。其成果就是IBSEN,一个用于情节与导航的脑系统中想象的概念模型。文章最后通过分析本期特刊中的其他论文,来评估它们的研究结果与本文所提出研究的相关程度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/579e/7152744/ac4ee04096e8/422_2020_829_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验