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
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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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