Closed-loop Neural Interface Technologies (Close-NIT) Network Plus
Closed-loop Neural Interface Technologies (Close-NIT) Network Plus
批准号:
EP/W035081/1
负责人:
Andrew Jackson
金额:
$140.95万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
人脑是我们所知道的最复杂的动力系统。它的解剖结构的特点是在一千亿个细胞之间的双向连接和循环反馈回路,这些细胞支持信息的表达、处理和存储。它的行为是通过与身体、环境和其他个体的双向连接和感觉运动反馈回路来表达的,这反过来又改变了大脑内部连接的强度,使我们能够学习、理解、移动和交流。现在,在我们的进化史上,我们第一次开始用新的人工连接来增强这些生物连接,以修复、恢复和增强我们的神经回路和认知功能。神经接口允许电子电路感知和处理大脑活动,然后通过神经刺激将信号实时返回神经系统,在大脑和技术之间形成直接的“闭环”。潜在的应用包括神经假体装置,以取代因损伤而失去的连接,神经康复装置,以驱动大脑回路的塑性变化,和神经调节装置,以控制与许多神经系统疾病相关的异常活动模式。在未来,我们可能能够调节我们的精神状态,以新的方式与计算机和机器进行交流,并最终融合生物智能和人工智能。然而,尽管目前围绕神经技术的炒作,有许多未回答的问题是由神经接口的闭环应用所特有的。其中一些是技术性的,比如我们如何最好地同时监控和操纵大脑的电活动而不产生串扰?有些是计算性的,比如我们应该使用什么算法来将感知到的大脑活动转化为刺激,以及这些如何在可穿戴或植入设备上实时实现?有些是科学的,比如神经回路如何对闭环接口做出反应,以及如何利用这一点来获得治疗益处?最重要的是,还有一些伦理问题,比如我们如何确保这些技术是安全的、有益的,并尊重用户的自主性和个性。虽然科学传统上通过孤立地解决问题来进步,但闭环接口需要跨学科工作的范式转变。特别是,我们试图揭示只有在大脑和技术之间的实时双向交互中才能揭示的新兴现象,科学机制和临床应用。因此,我们将建立一个网络,将来自学术界、工业界和医学界的专家联系起来,以解决闭环神经接口面临的关键挑战,加速科学和技术进步,同时与伦理学家、用户和公众合作,确保我们负责任地进入神经工程的未来。
英文摘要
The human brain is the most complex dynamical system that we know of. Its anatomical structure is characterised by bidirectional connections and recurrent feedback loops between a hundred billion cells that support the representation, processing and storage of information. Its behaviour is expressed through bidirectional connections and sensorimotor feedback loops with the body, the environment and other individuals, which in turn alter the strength of connections within the brain, allowing us to learn, understand, move and communicate. Now, for the first time in our evolutionary history, we are beginning to augment these biological connections with new, artificial connections to repair, restore and enhance our neural circuits and cognitive functions. Neural interfaces allow brain activity to be sensed and processed by electronic circuitry, which can then return signals back to the nervous system in real-time through neurostimulation to form a direct 'closed loop' between the brain and technology. Potential applications include neuroprosthetic devices to replace connections lost through injury, neurorehabilitation devices to drive plastic changes in brain circuits, and neuromodulation devices to control the aberrant patterns of activity associated with many neurological disorders. In future, we may be able to regulate our mental states, communicate in new ways with computers and machines, and ultimately merge biological and artificial intelligence. However, despite the current hype around neurotechnology, there are many unanswered questions that are uniquely posed by closed-loop applications of neural interfaces. Some of these are technological in nature, such as how best can we simultaneously monitor and manipulate electrical brain activity without cross-talk? Some are computational, such as what algorithms should we use to transform sensed brain activity into stimulation and how can these be implemented in real-time on wearable or implantable devices? Some are scientific, such as how do neural circuits respond to closed-loop interfaces and how can this be harnessed for therapeutic benefit? Most importantly, there are ethical questions, such as how can we ensure these technologies are safe, beneficial and respectful of the autonomy and individuality of users. While science traditionally progresses by tackling problems in isolation, closed-loop interfaces require a paradigm shift in transdisciplinary working. In particular, we seek to uncover the emergent phenomena, scientific mechanisms and clinical applications that can only be revealed in real-time bidirectional interactions between brains and technology. Therefore, we will build a network to connect experts from academia, industry and medicine to address the key challenges facing closed-loop neural interfaces, accelerating scientific and technological progress while engaging with ethicists, users and the public to ensure we advance responsibly into the neuroengineered future.
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Ultra Low Power Implantable Platform for Next Generation Neural Interfaces
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Optimal feedback control of a neuromotor interface
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Functional studies of mutant nucleases in a genetic model of inflammatory and viral disease.
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依托单位:
Virus and Host Interactions of the Nucleocapsid Proteins Encoded by a Plant Nucleorhabdovirus
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Protein Interactions During Replication of a Plant Rhabodovirus
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依托单位:
国内基金
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