实现人类感官增强:评估感知、大脑表征和主观体验中新信号整合的认知神经科学框架

Marko Nardini, Meike Scheller, Melissa Ramsay, Olaf Kristiansen, Chris Allen
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引用次数: 0

摘要

新型可穿戴设备和技术为增强或替代人类的感知能力提供了前所未有的空间。然而,在婴儿早期的敏感期,大脑处理过程可以灵活重组以使用新的感官信号,但到了晚年,这种灵活性就不那么明显了,因此将新信号整合到成年人的感知中是一项重大挑战。我们认为,以认知神经科学为基础的方法对于最大限度地发挥新感官技术的真正潜力至关重要。在此,我们提出了一个框架,用于测量和评估新信号在现有感知和体验结构中的整合程度。作为测试平台,我们利用实验室任务让健康志愿者学习新的、增强的感知-运动技能。我们描述了一整套(i)感知功能(心理物理学)、(ii)神经表征(fMRI/解码)和(iii)主观体验(定性访谈/微观现象学)的测量方法,旨在测试关于新学习的信号如何整合到感知和体验中的假设。作为概念验证,我们提供了示例数据,说明这种方法如何使我们能够测量感知、神经处理和主观体验的变化。我们认为,这一框架与有针对性的优化训练和学习方法相结合,为开发和优化人类感官增强和替代的新方法提供了必要的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Human Sensory Augmentation: A Cognitive Neuroscience Framework for Evaluating Integration of New Signals within Perception, Brain Representations, and Subjective Experience

New wearable devices and technologies provide unprecedented scope to augment or substitute human perceptual abilities. However, the flexibility to reorganize brain processing to use novel sensory signals during early sensitive periods in infancy is much less evident at later ages, making integration of new signals into adults’ perception a significant challenge. We believe that an approach informed by cognitive neuroscience is crucial for maximizing the true potential of new sensory technologies. Here, we present a framework for measuring and evaluating the extent to which new signals are integrated within existing structures of perception and experience. As our testbed, we use laboratory tasks in which healthy volunteers learn new, augmented perceptual-motor skills. We describe a suite of measures of (i) perceptual function (psychophysics), (ii) neural representations (fMRI/decoding), and (iii) subjective experience (qualitative interview/micro-phenomenology) targeted at testing hypotheses about how newly learned signals become integrated within perception and experience. As proof of concept, we provide example data showing how this approach allows us to measure changes in perception, neural processing, and subjective experience. We argue that this framework, in concert with targeted approaches to optimizing training and learning, provides the tools needed to develop and optimize new approaches to human sensory augmentation and substitution.

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