Developing an Adaptive Cognitive Prosthetic to Replace Damaged Brain Regions

开发自适应认知假体来替代受损的大脑区域

• 批准号: 8755948
• 负责人: Timothy J. Buschman
• 金额: $ 243万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2019-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8755948
• 关键词: Affect; Algorithms; Animal Model; Behavioral; Brain; Brain Injuries; Brain region; Bypass; Cognitive; Economics; Hemispatial Neglect; Individual; Injury; Learning; Modeling; Monitor; Monkeys; Mus; Neurons; Neurophysiology - biologic function; Parietal; Parietal Lobe; Pattern; Population; Positioning Attribute; Prevalence; Prosthesis; Quality of life; Stroke; Structure; Testing; Tissues; Traumatic Brain Injury; United States; cognitive function; cost; economic cost; effective therapy; experience; neural patterning; novel; public health relevance; relating to nervous system

DESCRIPTION (provided by applicant): Traumatic brain injuries severely reduce the quality of life for affected individuals and carry significant societal and economic costs. Despite the prevalence of these injuries, there is currently no effective treatment. Here we propose to develop a novel treatment for permanent brain damage: an Adaptive Cognitive Prosthetic that will learn to replace the neural function that was lost due to a brain injury. To effectively bypas the damaged cortical region, our proposed cognitive prosthetic will mimic its structure: it will record neural activity from other brain regions, transform this activity according to the lost cognitive function, and then stimulate unaffected brain regions in order to convey the result. Here we propose to develop the three core components necessary for achieving such a prosthetic. First, neural activity must be recorded from unaffected brain regions. This will provid the input to the prosthetic, allowing it to monitor the current brain state. Second, the prosthetic must be able to act upon the brain, stimulating neural tissue in undamaged brain regions in order to bypass the damaged brain region. Finally, an adaptive algorithm must bridge the previous two components: transforming the observed brain state to a pattern of stimulation in order to mimic the to-be-replaced brain region. However, the exact pattern of stimulation previously associated with each state is unknowable and therefore must be learned. To this end, we propose a novel, hierarchical, learning algorithm that can discover the appropriate stimulation patterns. My lab is uniquely positioned to develop this prosthetic. We have extensive experience recording from large populations of neurons (the first component) and have developed a novel paradigm for stimulating patterns of neural activity (the second component). In the current proposal we will develop the adaptive algorithm, testing its efficacy in mice. Finally, we will combine all of the necessary components to test the cognitive prosthetic in a monkey-model of hemispatial neglect, a common behavioral deficit following parietal stroke.

描述(由申请人提供)：创伤性脑损伤严重降低了受影响个人的生活质量，并带来了巨大的社会和经济代价。尽管这些伤害很普遍，但目前还没有有效的治疗方法。在这里，我们建议开发一种新的治疗永久性脑损伤的方法：一种自适应认知假体，它将学习取代因脑损伤而丧失的神经功能。为了有效地绕过受损的皮质区域，我们提出的认知假体将模仿其结构：它将记录其他大脑区域的神经活动，根据丧失的认知功能转换这种活动，然后刺激未受影响的大脑区域，以传达结果。在这里，我们建议开发实现这种假体所需的三个核心组件。首先，必须记录未受影响的大脑区域的神经活动。这将为假肢提供输入，使其能够监控当前的大脑状态。第二，假肢 必须能够作用于大脑，刺激未受损脑区的神经组织，以便绕过受损的脑区。最后，自适应算法必须连接前两个部分：将观察到的大脑状态转换为刺激模式，以模拟要替换的大脑区域。然而，之前与每种状态相关的确切刺激模式是未知的，因此必须学习。为此，我们提出了一种新颖的、分层的、能够发现合适的刺激模式的学习算法。我的实验室在研发这种假肢方面具有独特的优势。我们有丰富的记录大量神经元的经验(第一部分)，并开发了一种新的范式来刺激神经活动的模式(第二部分)。在目前的方案中，我们将开发自适应算法，在小鼠身上测试其有效性。最后，我们将结合所有必要的组件，在半空间忽视的猴子模型中测试认知假体，这是顶叶中风后常见的行为缺陷。