美国加州大学Gopala K. Anumanchipalli研究小组发现一种流脑-声神经假体来恢复自然的交流。相关论文发表在2025年3月31日出版的《自然—神经科学》杂志上。

在这里，研究团队对一个患有严重麻痹和关节炎的临床试验参与者的语言感觉运动皮层的高密度表面记录进行主题化，以驱动一个连续流的自然语音合成器。课题组人员设计并主题化了深度学习递归神经网络换能器模型，以80毫秒为增量进行神经解码，实现针对参与者损伤前语音个性化的在线大词汇可理解流利语音合成。离线时，模型显示了隐式语音检测能力，可以无限地连续解码语音，使解码器的主题不间断，进一步提高了速度。他们的框架也成功地推广到其他无声语音接口，包括单单元记录和肌电图。他们的发现引入了一种语言-神经假肢模式，以恢复瘫痪患者的自然语言交流。

据了解，自然的口头交流是即时发生的。讲话延迟超过几秒钟就会破坏对话的自然流畅。这使得瘫痪患者难以参与有意义的对话，可能导致孤立和疏远的感觉。

附：英文原文

Title: A streaming brain-to-voice neuroprosthesis to restore naturalistic communication

Author: Littlejohn, Kaylo T., Cho, Cheol Jun, Liu, Jessie R., Silva, Alexander B., Yu, Bohan, Anderson, Vanessa R., Kurtz-Miott, Cady M., Brosler, Samantha, Kashyap, Anshul P., Hallinan, Irina P., Shah, Adit, Tu-Chan, Adelyn, Ganguly, Karunesh, Moses, David A., Chang, Edward F., Anumanchipalli, Gopala K.

Issue&Volume: 2025-03-31

Abstract: Natural spoken communication happens instantaneously. Speech delays longer than a few seconds can disrupt the natural flow of conversation. This makes it difficult for individuals with paralysis to participate in meaningful dialogue, potentially leading to feelings of isolation and frustration. Here we used high-density surface recordings of the speech sensorimotor cortex in a clinical trial participant with severe paralysis and anarthria to drive a continuously streaming naturalistic speech synthesizer. We designed and used deep learning recurrent neural network transducer models to achieve online large-vocabulary intelligible fluent speech synthesis personalized to the participant’s preinjury voice with neural decoding in 80-ms increments. Offline, the models demonstrated implicit speech detection capabilities and could continuously decode speech indefinitely, enabling uninterrupted use of the decoder and further increasing speed. Our framework also successfully generalized to other silent-speech interfaces, including single-unit recordings and electromyography. Our findings introduce a speech-neuroprosthetic paradigm to restore naturalistic spoken communication to people with paralysis.

DOI: 10.1038/s41593-025-01905-6

Source: https://www.nature.com/articles/s41593-025-01905-6