Bikić Antonio, Pernice Wolfram H P
Department for Physics and Astronomy, Kirchhoff Institute for Physics, Heidelberg University, Baden-Württemberg, 69120 Heidelberg, Germany.
Department of Physics, CeNTech - Center for Nanotechnology, University of Münster, North Rhine-Westphalia, 48149 Münster, Germany.
Patterns (N Y). 2025 Apr 29;6(7):101238. doi: 10.1016/j.patter.2025.101238. eCollection 2025 Jul 11.
Multisensory perception produces vast amounts of data requiring efficient processing. This paper focuses on the multisensory example of touch in biological and artificial systems. We integrate philosophical theories of multisensory perception with neuromorphic hardware and demonstrate how classical sensory integration concepts can enhance artificial sensory systems. This approach bridges theoretical neuroscience and computational applications using philosophical tools. We contrast human touch perception, involving feature binding, with artificial perception in neuromorphic computing, where such integration is absent. Two theoretical frameworks are of interest, feature binding and modalities as conventional kinds, in evaluating their relevance to artificial touch. Our findings suggest that a hardware-tailored adaptation of the conventional modalities approach accurately reflects artificial touch perception. Unlike human perception, artificial systems process sensory data separately, lacking binding mechanisms. We explore the implications of these differences, highlighting challenges in replicating human sensory experiences and the role of subjective experience in perception.
多感官感知会产生大量需要高效处理的数据。本文聚焦于生物和人工系统中触觉这一多感官示例。我们将多感官感知的哲学理论与神经形态硬件相结合，并展示经典的感官整合概念如何增强人工感官系统。这种方法利用哲学工具架起了理论神经科学与计算应用之间的桥梁。我们将涉及特征绑定的人类触觉感知与神经形态计算中的人工感知进行对比，在神经形态计算中不存在这种整合。在评估它们与人工触觉的相关性时，有两个理论框架值得关注，即特征绑定和作为传统种类的模态。我们的研究结果表明，对传统模态方法进行硬件定制的调整能够准确反映人工触觉感知。与人类感知不同，人工系统分别处理感官数据，缺乏绑定机制。我们探讨了这些差异的影响，强调了复制人类感官体验所面临的挑战以及主观体验在感知中的作用。
