移动脑/身体成像:基于4E认知视角的研究项目实施的挑战和机遇

IF 1.2 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Aitana Grasso-Cladera, Stefanella Costa-Cordella, Alejandra Rossi, Nikolas F Fuchs, Francisco J Parada
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引用次数: 1

摘要

认知动力学是多模态的,它们需要整合实时反馈以适应和适当。然而,认知研究仍然主要依赖于单模态范式,在基于实验室的静态情境中使用简单的运动任务。本文通过提出基于嵌入、嵌入、扩展和动态视角的移动脑/身体成像方法来解决这一限制,该方法补充了传统的实验室工作,同时也促进了生态有效的应用。首先,我们简要回顾了用于获取自然认知过程中脑/身体系统功能和结构图像的移动脑/身体成像技术。具体来说:移动认知电生理学、移动功能神经血管动力学和移动行为测量。其次,我们回顾了移动脑/体成像/4E在智利的发展。最后,我们讨论了挑战和机遇。我们的结论是,尽管这种新的认知/方法方法很有前途,但需要更大的可移植性、强大的设备和数据分析工具,以整合来自大脑/身体的信号。未来的实验设计需要重新考虑其潜在的逻辑,并通过修改实验进行的物理空间来增加其生态有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mobile Brain/Body Imaging: Challenges and opportunities for the implementation of research programs based on the 4E perspective to cognition

Cognitive dynamics are multimodal, and they need to integrate real-time feedback to be adaptive and appropriate. However, cognition research still relies on mostly unimodal paradigms using simple motor tasks in laboratory-based static situations. This paper addresses this limitation by presenting the Mobile Brain/Body Imaging approach based on the Embodied, Embedded, Extended, and Enactive perspective, which complements traditional laboratory work while also facilitating ecologically valid applications. First, we briefly review Mobile Brain/Body Imaging technologies used to obtain functional and structural images of the Brain/Body System during natural cognition. Specifically: mobile cognitive electrophysiology, mobile functional neurovascular dynamics, and mobile behavioral measurements. Second, we review the development of Mobile Brain/Body Imaging/4E in Chile. Finally, we discuss challenges and opportunities. We conclude that although this new epistemic/methodological approach is promising, there is a need for greater portability, robust equipment, and data-analysis tools that can integrate signals from the brain/body-in-the-world system. Future experimental designs need to re-consider their underlying logic and increase their ecological validity by perhaps-modifying the physical spaces in which experiments are conducted.

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来源期刊
Adaptive Behavior
Adaptive Behavior 工程技术-计算机:人工智能
CiteScore
4.30
自引率
18.80%
发文量
34
审稿时长
>12 weeks
期刊介绍: _Adaptive Behavior_ publishes articles on adaptive behaviour in living organisms and autonomous artificial systems. The official journal of the _International Society of Adaptive Behavior_, _Adaptive Behavior_, addresses topics such as perception and motor control, embodied cognition, learning and evolution, neural mechanisms, artificial intelligence, behavioral sequences, motivation and emotion, characterization of environments, decision making, collective and social behavior, navigation, foraging, communication and signalling. Print ISSN: 1059-7123
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