Decoding Continuous Character-based Language from Non-invasive Brain Recordings

• URL: http://arxiv.org/abs/2403.11183v2
• Date: Tue, 19 Mar 2024 10:09:20 GMT
• Title: Decoding Continuous Character-based Language from Non-invasive Brain Recordings
• Authors: Cenyuan Zhang, Xiaoqing Zheng, Ruicheng Yin, Shujie Geng, Jianhan Xu, Xuan Gao, Changze Lv, Zixuan Ling, Xuanjing Huang, Miao Cao, Jianfeng Feng,
• Abstract summary: We propose a novel approach to decoding continuous language from single-trial non-invasive fMRI recordings. A character-based decoder is designed for the semantic reconstruction of continuous language characterized by inherent character structures. The ability to decode continuous language from single trials across subjects demonstrates the promising applications of non-invasive language brain-computer interfaces.
• Score: 33.11373366800627
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Deciphering natural language from brain activity through non-invasive devices remains a formidable challenge. Previous non-invasive decoders either require multiple experiments with identical stimuli to pinpoint cortical regions and enhance signal-to-noise ratios in brain activity, or they are limited to discerning basic linguistic elements such as letters and words. We propose a novel approach to decoding continuous language from single-trial non-invasive fMRI recordings, in which a three-dimensional convolutional network augmented with information bottleneck is developed to automatically identify responsive voxels to stimuli, and a character-based decoder is designed for the semantic reconstruction of continuous language characterized by inherent character structures. The resulting decoder can produce intelligible textual sequences that faithfully capture the meaning of perceived speech both within and across subjects, while existing decoders exhibit significantly inferior performance in cross-subject contexts. The ability to decode continuous language from single trials across subjects demonstrates the promising applications of non-invasive language brain-computer interfaces in both healthcare and neuroscience.

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