交叉模态
多传感器集成
计算机科学
感觉系统
感知
人工神经网络
人机交互
神经科学
视觉感受
人工智能
心理学
作者
Hongwei Tan,Yifan Zhou,Quanzheng Tao,Johanna Rosén,Sebastiaan van Dijken
标识
DOI:10.1038/s41467-021-21404-z
摘要
Abstract The integration and interaction of vision, touch, hearing, smell, and taste in the human multisensory neural network facilitate high-level cognitive functionalities, such as crossmodal integration, recognition, and imagination for accurate evaluation and comprehensive understanding of the multimodal world. Here, we report a bioinspired multisensory neural network that integrates artificial optic, afferent, auditory, and simulated olfactory and gustatory sensory nerves. With distributed multiple sensors and biomimetic hierarchical architectures, our system can not only sense, process, and memorize multimodal information, but also fuse multisensory data at hardware and software level. Using crossmodal learning, the system is capable of crossmodally recognizing and imagining multimodal information, such as visualizing alphabet letters upon handwritten input, recognizing multimodal visual/smell/taste information or imagining a never-seen picture when hearing its description. Our multisensory neural network provides a promising approach towards robotic sensing and perception.
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