CRCNS: Avian Model for Neural Activity Driven Speech Prostheses

了解人类发声的物理，计算和理论基础 沟通，言语，是至关重要的，以提高理解的声音，讲话和语言 疾病和失调，并改善其诊断，治疗和预防。满足这一 挑战需要了解发声运动控制的神经和感觉运动机制。 我们的项目将直接调查参与的神经和感觉运动机制， 产生复杂的、自然的、有声的通信信号。我们的成果将直接提高 脑机接口技术的发展，将加速 假肢和其他辅助/增强技术 由于受伤或疾病而造成的缺陷。我们将开发一种发音假体， 将皮层感觉运动和发声运动控制区的信号转化为发声通信信号 实时输出。利用非人类灵长类动物作为脑机接口的成功基础 对于一般的运动控制，假肢将在鸣禽身上开发，鸣禽的声音丰富， 习得的发声与人类语言有许多共同的特征。因为鸣禽的声音 该装置在功能上和解剖学上类似于人类喉，并且皮质区域 与人类大脑中控制语言运动的区域非常相似， 为拟议的研究提供了理想的模型。除了将我们的工作应用于人类的声音之外， 和语音，发声假肢的发展将使新的语音相关的研究， 鸣禽模型，可以揭示发声学习和生产的基本机制。在 在项目的第一阶段，我们收集了大量同时记录的神经活动数据集， 发声在第二阶段，我们将应用机器学习和人工智能技术， 开发将神经记录映射到声音输出的算法，使我们能够估计预期的 直接从神经数据中提取声音。在第三阶段，我们将开发计算基础设施， 实时运行这些算法，从神经活动中预测预期的发声， 动物正在积极地发出这些声音。在第四阶段，我们将测试 通过用我们的假肢系统的输出来代替鸟自己的发声。 成功将为这些技术在人类身上的测试和向多个领域的转化奠定基础。 辅助设备。除了我们的研究目标，该项目将从事研究生， 通过开发新颖的教育模块， 向学生介绍脑机接口和跨学科研究， 工程学和基础科学。

Understanding the physical, computational, and theoretical bases of human vocal communication, speech, is crucial to improved comprehension of voice, speech and language diseases and disorders, and improving their diagnosis, treatment and prevention. Meeting this challenge requires knowledge of the neural and sensorimotor mechanisms of vocal motor control. Our project will directly investigate the neural and sensorimotor mechanisms involved in the production of complex, natural, vocal communication signals. Our results will directly enhance brain-computer interface technology for communication and will accelerate the development of prostheses and other assistive/augmentative technologies for individuals with communications deficits due to injury or disease. We will develop a vocal prosthetic that directly translates neural signals in cortical sensorimotor and vocal-motor control regions into vocal communication signals output in real-time. Building on success using non-human primates for brain computer interfaces for general motor control, the prosthetic will be developed in songbirds, whose acoustically rich, learned vocalizations share many features with human speech. Because the songbird vocal apparatus is functionally and anatomically similar to the human larynx, and the cortical regions that control it are closely analogous to speech motor-control areas of the human brain, songbirds offer an ideal model for the proposed studies. Beyond the application of our work to human voice and speech, development of the vocal prosthetic will enable novel speech-relevant studies in the songbird model that can reveal fundamental mechanisms of vocal learning and production. In the first stage of the project, we collect a large data set of simultaneously recorded neural activity and vocalizations. In stage two, we will apply machine learning and artificial intelligence techniques to develop algorithms that map neural recordings to vocal output and enable us to estimate intended vocalizations directly from neural data. In stage three, we will develop computing infrastructure to run these algorithms in real-time, predicting intended vocalizations from neural activity as the animal is actively producing these vocalizations. In stage four, we will test the effectiveness of the prosthetic by substituting the bird’s own vocalization with the output from our prosthetic system. Success will set the stage for testing of these technologies in humans and translation to multiple assistive devices. In addition to our research goals, the project will engage graduate, undergraduate, and high school students through the development of novel educational modules that introduce students to brain machine interface and multidisciplinary studies that span engineering and the basic sciences.