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文献精选 > 近年高分"脑机接口"研究（IF≥30，近5年）

An Accurate and Rapidly Calibrating Speech Neuroprosthesis. ​

文献信息 ​

DOI10.1056/NEJMoa2314132
PMID39141853
期刊The New England journal of medicine
影响因子78.5
JCR 分区Q1
发表年份2024
被引次数38
关键词脑机接口, 神经假体, 肌萎缩侧索硬化症
文献类型Journal Article, Case Reports, Research Support, U.S. Gov't, Non-P.H.S., Research Support, N.I.H., Extramural
ISSN0028-4793
页码609-618
期号391(7)
作者Nicholas S Card, Maitreyee Wairagkar, Carrina Iacobacci, Xianda Hou, Tyler Singer-Clark, Francis R Willett, Erin M Kunz, Chaofei Fan, Maryam Vahdati Nia, Darrel R Deo, Aparna Srinivasan, Eun Young Choi, Matthew F Glasser, Leigh R Hochberg, Jaimie M Henderson, Kiarash Shahlaie, Sergey D Stavisky, David M Brandman

一句话小结 ​

本研究探讨了一种脑-计算机接口技术在一名患有肌萎缩侧索硬化症（ALS）患者中的应用，经过短时间的训练，该技术在试图说话时的皮层活动解码达到了高达99.6%的准确率，且在经过额外训练后在更大词汇量下仍保持90.2%的准确率。这一成果为瘫痪患者提供了有效的交流手段，具有重要的临床意义。

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脑机接口 · 神经假体 · 肌萎缩侧索硬化症

摘要 ​

背景
脑-计算机接口可以通过将与尝试语言相关的皮层活动转化为计算机屏幕上的文本，从而为瘫痪患者提供交流的可能性。然而，脑-计算机接口的交流受到广泛的训练要求和有限准确性的限制。

方法
一名45岁患有肌萎缩侧索硬化症（ALS）的男性，因四肢无力和严重构音障碍，于疾病发作5年后接受了四个微电极阵列的外科植入，这些阵列植入在他左侧腹侧前中央回，记录了256个皮质内电极的神经活动。我们报告了他在尝试说话时的皮层神经活动解码结果，包括在提示和非结构化对话环境下的表现。解码后的单词在屏幕上显示，并通过旨在模仿其ALS前声音的文本转语音软件进行发声。

结果
在使用的第一天（手术后25天），该神经假体在50个单词的词汇量下达到了99.6%的准确率。神经假体的校准需要30分钟的皮层录音，在此期间参与者尝试说话，随后进行处理。第二天，经过额外1.4小时的系统训练后，神经假体在125,000个单词的词汇量下达到了90.2%的准确率。随着进一步的训练数据，神经假体在手术植入后持续保持了97.5%的准确率，参与者在自我节奏的对话中以每分钟约32个单词的速度进行了交流，总累计使用时间超过248小时。

结论
在一名患有ALS和严重构音障碍的患者中，皮质内语言神经假体在经过简短训练后达到了恢复对话交流的适当性能水平。（由国防部健康事务助理秘书办公室及其他机构资助；BrainGate2 临床试验注册号，NCT00912041。）

英文摘要 ​

BACKGROUND Brain-computer interfaces can enable communication for people with paralysis by transforming cortical activity associated with attempted speech into text on a computer screen. Communication with brain-computer interfaces has been restricted by extensive training requirements and limited accuracy.

METHODS A 45-year-old man with amyotrophic lateral sclerosis (ALS) with tetraparesis and severe dysarthria underwent surgical implantation of four microelectrode arrays into his left ventral precentral gyrus 5 years after the onset of the illness; these arrays recorded neural activity from 256 intracortical electrodes. We report the results of decoding his cortical neural activity as he attempted to speak in both prompted and unstructured conversational contexts. Decoded words were displayed on a screen and then vocalized with the use of text-to-speech software designed to sound like his pre-ALS voice.

RESULTS On the first day of use (25 days after surgery), the neuroprosthesis achieved 99.6% accuracy with a 50-word vocabulary. Calibration of the neuroprosthesis required 30 minutes of cortical recordings while the participant attempted to speak, followed by subsequent processing. On the second day, after 1.4 additional hours of system training, the neuroprosthesis achieved 90.2% accuracy using a 125,000-word vocabulary. With further training data, the neuroprosthesis sustained 97.5% accuracy over a period of 8.4 months after surgical implantation, and the participant used it to communicate in self-paced conversations at a rate of approximately 32 words per minute for more than 248 cumulative hours.

CONCLUSIONS In a person with ALS and severe dysarthria, an intracortical speech neuroprosthesis reached a level of performance suitable to restore conversational communication after brief training. (Funded by the Office of the Assistant Secretary of Defense for Health Affairs and others; BrainGate2 ClinicalTrials.gov number, NCT00912041.).

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主要研究问题 ​

  1. 在ALS患者中，神经假体的准确性和训练时间是否会因个体差异而有所不同？
  2. 除了语音恢复，神经假体在其他类型的神经疾病患者中是否有应用潜力？
  3. 该研究中使用的微电极阵列与其他类型的脑机接口相比，有何优缺点？
  4. 在未来的研究中，如何进一步提高神经假体的词汇量和识别准确性？
  5. 患者在使用神经假体进行沟通时，心理和情感上的影响有哪些，如何进行评估？

核心洞察 ​

研究背景和目的 ​

脑机接口（BCI）技术可以将与言语尝试相关的皮层活动转化为计算机屏幕上的文本，从而为瘫痪患者提供沟通手段。然而，目前的BCI技术受到 extensive training requirements 和 limited accuracy 的限制。本文旨在评估一种新型的皮层言语神经假体在一名重度肌萎缩侧索硬化症（ALS）患者中的应用效果，探索其在恢复言语交流中的潜力。

主要方法/材料/实验设计 ​

研究对象为一名45岁的ALS患者，具备四肢无力和严重构音障碍。研究方法包括以下步骤：

  1. 手术植入：在患者左侧腹侧中央回植入四个微电极阵列，记录256个皮层电极的神经活动。
  2. 数据采集：在提示和非结构化对话环境中，记录患者尝试发声时的皮层活动。
  3. 信号解码：将记录的神经活动解码为文本，并通过文本转语音软件进行语音输出。

以下是该研究的技术路线图：

Mermaid diagram

关键结果和发现 ​

  • 初始准确性：在手术后25天的首次使用中，神经假体以50个词汇的基础实现了99.6%的准确率。
  • 系统校准：校准过程需进行30分钟的皮层记录，随后进行数据处理。
  • 词汇扩展：经过1.4小时的额外系统训练后，第二天的准确率为90.2%，词汇量扩展至125,000个词。
  • 持续性能：在手术后8.4个月内，神经假体的准确率保持在97.5%，患者以每分钟约32个词的速度进行自我节奏对话，总使用时间超过248小时。

主要结论/意义/创新性 ​

本研究表明，针对ALS患者的皮层言语神经假体能够在短时间训练后恢复会话沟通能力，展现出极高的准确性和使用效率。这一技术为重度构音障碍患者提供了新的沟通方式，具有重要的临床意义和创新性，可能改变传统的沟通辅助技术。

研究局限性和未来方向 ​

  • 局限性：本研究仅在一名患者中进行，样本量较小，结果的普遍性需要进一步验证。
  • 未来方向：未来研究应扩展到更多患者，探索不同类型神经疾病的适用性，以及进一步优化系统的训练和解码算法，以提高其在临床应用中的有效性和可靠性。

参考文献 ​

  1. A Neurosurgical Functional Dissection of the Middle Precentral Gyrus during Speech Production. - Alexander B Silva;Jessie R Liu;Lingyun Zhao;Deborah F Levy;Terri L Scott;Edward F Chang - The Journal of neuroscience : the official journal of the Society for Neuroscience (2022)
  2. Stable Decoding from a Speech BCI Enables Control for an Individual with ALS without Recalibration for 3 Months. - Shiyu Luo;Miguel Angrick;Christopher Coogan;Daniel N Candrea;Kimberley Wyse-Sookoo;Samyak Shah;Qinwan Rabbani;Griffin W Milsap;Alexander R Weiss;William S Anderson;Donna C Tippett;Nicholas J Maragakis;Lora L Clawson;Mariska J Vansteensel;Brock A Wester;Francesco V Tenore;Hynek Hermansky;Matthew S Fifer;Nick F Ramsey;Nathan E Crone - Advanced science (Weinheim, Baden-Wurttemberg, Germany) (2023)
  3. New and emerging access technologies for adults with complex communication needs and severe motor impairments: State of the science. - Susan Koch Fager;Melanie Fried-Oken;Tom Jakobs;David R Beukelman - Augmentative and alternative communication (Baltimore, Md. : 1985) (2019)
  4. In pursuit of off-task thought: mind wandering-performance trade-offs while reading aloud and color naming. - David R Thomson;Derek Besner;Daniel Smilek - Frontiers in psychology (2013)
  5. Direct speech reconstruction from sensorimotor brain activity with optimized deep learning models. - Julia Berezutskaya;Zachary V Freudenburg;Mariska J Vansteensel;Erik J Aarnoutse;Nick F Ramsey;Marcel A J van Gerven - Journal of neural engineering (2023)
  6. Generalizable spelling using a speech neuroprosthesis in an individual with severe limb and vocal paralysis. - Sean L Metzger;Jessie R Liu;David A Moses;Maximilian E Dougherty;Margaret P Seaton;Kaylo T Littlejohn;Josh Chartier;Gopala K Anumanchipalli;Adelyn Tu-Chan;Karunesh Ganguly;Edward F Chang - Nature communications (2022)
  7. Speech synthesis from neural decoding of spoken sentences. - Gopala K Anumanchipalli;Josh Chartier;Edward F Chang - Nature (2019)
  8. Plug-and-Play Stability for Intracortical Brain-Computer Interfaces: A One-Year Demonstration of Seamless Brain-to-Text Communication. - Chaofei Fan;Nick Hahn;Foram Kamdar;Donald Avansino;Guy H Wilson;Leigh Hochberg;Krishna V Shenoy;Jaimie M Henderson;Francis R Willett - Advances in neural information processing systems (2023)
  9. Decoding spoken words using local field potentials recorded from the cortical surface. - Spencer Kellis;Kai Miller;Kyle Thomson;Richard Brown;Paul House;Bradley Greger - Journal of neural engineering (2010)
  10. Brain-to-text: decoding spoken phrases from phone representations in the brain. - Christian Herff;Dominic Heger;Adriana de Pesters;Dominic Telaar;Peter Brunner;Gerwin Schalk;Tanja Schultz - Frontiers in neuroscience (2015)

引用本文的文献 ​

  1. A flexible intracortical brain-computer interface for typing using finger movements. - Nishal P Shah;Matthew S Willsey;Nick Hahn;Foram Kamdar;Donald T Avansino;Chaofei Fan;Leigh R Hochberg;Francis R Willett;Jaimie M Henderson - bioRxiv : the preprint server for biology (2024)
  2. The speech neuroprosthesis. - Alexander B Silva;Kaylo T Littlejohn;Jessie R Liu;David A Moses;Edward F Chang - Nature reviews. Neuroscience (2024)
  3. Targeted deep brain stimulation of the motor thalamus improves speech and swallowing motor functions after cerebral lesions. - Elvira Pirondini;Erinn Grigsby;Lilly Tang;Arianna Damiani;Jonathan Ho;Isabella Montanaro;Sirisha Nouduri;Sara Trant;Theodora Constantine;Gregory Adams;Kevin Franzese;Bradford Mahon;Julie Fiez;Donald Crammond;Kaila Stipancic;Jorge Gonzalez-Martinez - Research square (2024)
  4. Brain Function, Learning, and Role of Feedback in Complete Paralysis. - Stefano Silvoni;Chiara Occhigrossi;Marco Di Giorgi;Dorothée Lulé;Niels Birbaumer - Sensors (Basel, Switzerland) (2024)
  5. Non-invasive brain-machine interface control with artificial intelligence copilots. - Johannes Y Lee;Sangjoon Lee;Abhishek Mishra;Xu Yan;Brandon McMahan;Brent Gaisford;Charles Kobashigawa;Mike Qu;Chang Xie;Jonathan C Kao - bioRxiv : the preprint server for biology (2024)
  6. Artificial Intelligence in Communication Sciences and Disorders: Introduction to the Forum. - Jordan R Green - Journal of speech, language, and hearing research : JSLHR (2024)
  7. Decoding the brain: From neural representations to mechanistic models. - Mackenzie Weygandt Mathis;Adriana Perez Rotondo;Edward F Chang;Andreas S Tolias;Alexander Mathis - Cell (2024)
  8. Reducing power requirements for high-accuracy decoding in iBCIs. - Brianna M Karpowicz;Bareesh Bhaduri;Samuel R Nason-Tomaszewski;Brandon G Jacques;Yahia H Ali;Robert D Flint;Payton H Bechefsky;Leigh R Hochberg;Nicholas AuYong;Marc W Slutzky;Chethan Pandarinath - Journal of neural engineering (2024)
  9. Speech motor cortex enables BCI cursor control and click. - Tyler Singer-Clark;Xianda Hou;Nicholas S Card;Maitreyee Wairagkar;Carrina Iacobacci;Hamza Peracha;Leigh R Hochberg;Sergey D Stavisky;David M Brandman - bioRxiv : the preprint server for biology (2024)
  10. Enabling electric field model of microscopically realistic brain. - Zhen Qi;Gregory M Noetscher;Alton Miles;Konstantin Weise;Thomas R Knösche;Cameron R Cadman;Alina R Potashinsky;Kelu Liu;William A Wartman;Guillermo Nunez Ponasso;Marom Bikson;Hanbing Lu;Zhi-De Deng;Aapo R Nummenmaa;Sergey N Makaroff - Brain stimulation (2025)

... (28 更多 篇文献)

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